DRI Project Report - Ice Cream Mix - Roberts Dairy Research... · National Ice Cream Mix Association ... • Global probiotic market is projected to reach $46.55 ... (Human Microbiome

NICMA Meeting

January 19, 2016Dr. Bob Roberts

Professor and Head of Food Science

1

Thank You!National Ice Cream Mix Association Dairy Processing Internship Award

First Award will be made in May of 2016

If you are interested in interns for your operations please contact me

2

Update on Dairy Research at Penn State

What’s going on in Happy Valley

3

Current Areas of Research• Dairy Chemistry

– Casein Micelle Structure-Dr. Federico Harte• Food Safety/Quality

– Development of Food Safety Training Programs for Artisanal Cheese Manufacturers-Dr. Cathy Cutter

– Improving Safety and Quality for Small Dairy Processors-Dr. Kerry Kaylegian

– Does Listeria Grow During Thawing of Ice Cream?-Dr. Sara Milillo• Manufacturing

– Consumer Acceptability of Ice Creams Made Replacing Fat with Maltodextrin-Dr. Bob Roberts/Dr. John Coupland/Dr. John Hayes

– High Pressure Jet Processing of Milk and Milk Products-Dr. Federico Harte

• Human Health– Assessment of Probiotic Delivery Vehicles-Dr. Bob Roberts– Casein as a delivery vehicle for hydrophobic molecules-Dr. Fede Harte

4

Fede Harte’s Research Areas

5

Biology of the Casein Micelle- structure and function

Effect of Environment- solvent effects

Analytical Tools

Effect of Processing- structure and function- novel interactions / applications

High Pressure Jet

xchanger

nozzle

HP line

HP Pump (600 MPa)

Polycarbonateenclosure

Pressure (MPa)0 100 200 300 400

G' (

Pa)

250

300

350

Yogurt from Homogenized milk

RAW

THERMAL

HPH

HPH + THERMAL

J. Dairy Sci. 2008, 91(10):3761-3767

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Delivery Systems

- Hypothesis: We can make the casein micelle a delivery system for “things” other than calcium phosphate

Casein micelle

Delivery Systems


Casein micelle

Hydrophobic probe

Delivery Systems


Casein micelle

Hydrophobic probe

Final System

NIH-NICHD“Milk-based nano-delivery system for

hydrophobic drugs in infants and children”

Overall objective: Use modified casein micelles from bovine milk as carrier systems for delivering the low

MW hydrophobic drug RITONAVIR

The case for Ritonavir

• Antiretroviral against HIV by Abbott (Norvir®)• Very low solubility in water (1 μg/mL at pH 6.8 for Form I)• High hydrophobicity (LogP~4.94)• Current formulation used in infants > 1 month contains 43%

ethanol• AWFUL flavor• Direct effect on stomach (mostly nausea, vomiting)• Exhibits polymorphism

RITONAVIR

1 μm

>300 MPa30 μm

RITONAVIR

SKIM MILK

0 MPa

Ritonavir release and digestion

0.0

10.0

20.0

30.0

40.0

50.0

60.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

110.0

0 1 2 3 4 5 6 7 8 9 10

Released R

IT (%)

Tota

l RIT

(rec

over

y %

)

Gastric digestion Duodenal digestion

5 ‘0 ’ 15 ‘ 30 ‘ 120 ‘ 15 ’ 60 ‘ 120 ‘30 ‘

Total ritonavir

From micelles after >300 MPa

Pharmaceutical Research 2015, 32(3):1055-1071

Other Areas of Interest

• Influence of HPJ processing on foaming• Influence of HPJ on ice cream functionality• Understanding effects of various salts and

solvents on casein micelle structure

A Study on the Effect of Delivery Vehicles on the

Efficacy of a Probiotic Strain Bifidobacterium

animalis subsp. lactis BB-12 in Humans

16

Probiotics• Probiotics are “live microorganisms that,

when administered in adequate amounts, confer a health benefit on the host” (FAO/WHO 2002, Hill et al. 2014)

– Alleviation of diarrhea– Modulation of host immune system– Reduction of allergic responses– Decreased bowel transit time– Prevention of infections

(de Vrese et al. 2008; Sherman et al. 2009, Hill et al. 2014)

17

en.wikipedia.org/wiki/Élie_Metchnikoff

Probiotics• Attributes of a successful probiotic:

– Survival in delivery vehicle – Tolerant to oxidative stress– Survival in human gastrointestinal tract – Health benefit associated with consumption– Non pathogenic

• Majority belong to the genera Lactobacillus or Bifidobacterium

• Global probiotic market is projected to reach $46.55 billion by 2020 (marketsandmarkets.com 2015)

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The genus Bifidobacterium• Gram positive

• Anaerobic

• Non-spore-forming

• Commonly added to fermented dairy products due to putative health benefits

• Currently contains 38 species and subspecies

– B. animalis subsp. lactis

– B. longum

– B. infantis

– B. breve

www.activia.com

With BifidusRegularis

With BB-12

www.delish.com/food/grocery-products

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20

B. animalis subsp. lactis BB-12

• Oxygen & bile tolerant (Garrigues et al. 2005, Jungersen et al. 2014)

• Generally Recognized As Safe (GRAS)• Safe in population ranging from infants to the elderly (Ouwehand et al.

2004)

• Modulate intestinal microbiota (Savard et al. 2011)

• Improve bowel function (Pitkala et al., 2007; Uchida et al., 2005; Nishida et al. 2004)

• Reduce gut transit time (Larsen et al. 2006)

• Improve immune function (Rizzardini et al. 2012)

www.chr-hansen.com

foodbizdaily.com

www.foodmayhem.com

Probiotic Delivery Vehicles

phyto-care.com

www.aligngi.com/21

• BB-12 survived and performed better in low fat milk than in orange juice (Saarela et al. 2006)

• Milk might be the preferred delivery matrix for certain probiotic strains (Lee et al. 2015)

22

Probiotic Functions of Interest

Gut transit time

Gut microbiota

Fecal SCFAs

23

Gut Transit Time (GTT)

• Gut transit time is simply the amount of time (hours) it takes for a meal to travel from the mouth, through the digestive tract and for its waste by-products to be eliminated through a bowel movement (Zaslavsky et al. 1998)

– Gastric emptying time

– Small bowel transit time

– Colonic transit time

• Negatively correlated with fecal SCFAs concentration (Lewis and Heaton, 1999)

http://northshorecolonics.com/the-digestive-system/

24

Gut Microbiota and Gut Microbiome

• “Gut microbiota” - the diverse and dynamic community of microorganisms in the gut (Grice and Segre 2012)

• “Fecal microbiota” - the diverse and dynamic community of microorganisms in the feces

• “Gut/fecal microbiome” - catalog of microbes and their genes present in the gut/feces (Human Microbiome Project Consortium 2012)

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Gut Microbiota and Health

• Alter host metabolism (Vijay-Kumar et al. 2010, Koren et al. 2012)

• Transmit colitis (Garrett et al. 2007)

• Modulate type I diabetes (Wen et al. 2008)

• Modulate host immune function (Clemente et al. 2012)

• Associated with susceptibility to influenza, colon cancer, retrovirus transmission, autoimmune demyelination, irritable bowel disease (IBD), and even behavior (Finegold et al. 2010, Gerritsen et al. 2011,

Marsland and Salami 2015)

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0 500 1000 1500 200019951997199920012003200520072009201120132015

Publications

Year

Recent Gut Microbiota Publications

• The vehicle used to deliver probiotic bacterium B. animalis subsp. lactis BB-12 (BB-12) into the body influences the performance of the probiotic in vivo

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Overall Hypothesis

Specific Aims• Aim 1: Develop three different BB-12 delivery systems (BB-12 added

before yogurt fermentation, BB-12 added after yogurt fermentation and BB-12 containing capsules) and study the viability of BB-12 in the yogurt drinks over 4 weeks of storage at 4°C

• Aim 2: Assess the influence of consumption of yogurt smoothie (with and without BB-12) and BB-12 containing capsules on participants’ gut transit time (GTT)

• Aim 3: Study the effect of the different interventions on participants’ fecal short chain fatty acid (SCFA) production

• Aim 4: Assess the influence of consumption of yogurt smoothie (with and without BB-12) and BB-12 containing capsules on participants’ fecal microbiota

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Randomized, 4-period crossover intervention

Overview of the Study

Screened subject group A, B, C, D

Immune markers

Fecal microbiota

Gut transit time

Capsule with BB-12

BB-12 added after fermentation

BB-12 added before fermentation

SmartPill capsule

16S rDNA sequencing

Blood & enzyme test

WithoutBB-12

CAPPOST PREYS

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Fecal SCFAs

GC

Lipids profile

Blood test

Log10 10 ± 0.5 CFU per 240 g serving or per capsule

Study Design

Subjects with irregular bowel

function

18-40 yearsBMI: 22-40

kg/m3

A

B

C

D

A

B

C

D

A

B

C

D

A

B

C

D

All subjectsFree-living

(4 weeks)

= Randomized to treatment sequence

= Data collection: fecal sample, blood draw, blood pressure, diaries & questionnaires

= 2-week compliance break; change to next treatment

Screening Period 1 Period 2 Period 3 Period 4

= Data collection: fecal sample only 30

Specific Aims• Aim 1: Develop three different BB-12 delivery systems

(BB-12 added before yogurt fermentation, BB-12 added after yogurt fermentation and BB-12 containing capsules) and study the viability of BB-12 in the yogurt drinks over 4 weeks of storage at 4°C




31

Milk selection

Dry matter standardization

Pasteurization

Homogenization

Cool down to 110oF

Heat treatment

32

Flow Diagram of Yogurt Smoothies

Blend

Inoculation (YF-L702)

Pectin, CSS, sugar, water

Fermentation

Stir and cool Yogurt to 70oF

Homogenization

Package

Slurry

Cool to 105oF

Heat to 185oF

Strawberry flavor

BB-12 for POST

BB-12 for PRE

Draw mix for PRE

Fermentation

Inoculate BB-12 (0.011% inoculation rate) into the PRE treatment

33

Slurry Production

34

Mixing and Homogenization

35

Sequence of Treatments

YS

POST

PRE

A

B

C

36

Packaging

37

Storage

38

Analyses of the Yogurt Smoothie Interventions

• Microbial analyses– Coliform– Survival of yogurt starter cultures– Survival of BB-12 over the 4-week shelf life

• Compositional analyses– Fat– Total solids

39

• Following manufacture of the yogurt smoothies and weekly throughout shelf life

• Track BB-12 concentration (Target: Log10 10 ± 0.5 CFU/240 g serving)

– Selective media• MRS-NNLP (MRS agar supplemented

with nalidixic acid, neomycin sulfate, lithium chloride, paromomycin sulfate, and cysteine hydrochloride

– Confirm BAL by PCR

40

Enumeration of BB-12

41

Specific Aim 1 - Results

42

BB-12 Increased Modestly During Yogurt Fermentation

Log10 CFU/gBB-12 in PRE before yogurt fermentation 8.01 ± 0.05b

BB-12 in PRE after yogurt fermentation 8.10 ± 0.04a

BB-12 in POST after yogurt fermentation 8.10 ± 0.03a

Data shown were mean ± SD from at least 4 replicates. Values in a column without a common letter are significantly different, P < 0.05

43

Component YS PRE POSTTotal solids (%) 20.92 ± 0.36b 21.58 ± 0.53a 20.96 ± 0.32b

Fat (%) 0.68 ± 0.07b 0.68 ± 0.07b 0.71 ± 0.07a

Data shown were mean ± SD from 30 batches. Values in a row without a common letter are significantly different, P < 0.05

Composition of the Yogurt Smoothies

44

TreatmentBB-12 concentration (Log10 CFU/serving)

Week 0 Week 1 Week 2 Week 3 Week 4

PRE 10.55 ±0.12Aa

10.43 ±0.13Ba

10.42 ±0.13Ba

10.34 ±0.13Ca

10.24 ±0.13Da

POST 10.50 ±0.14Ab

10.16 ±0.15Bb

10.03 ±0.20Cb

9.77 ±0.20Db

9.54 ±0.25Eb

Data shown were mean ± SD from 27 batches. Values in a column without a common lowercase letter are significantly different. Values in a row without a common UPPERCASE letter are significantly different, P < 0.05.

BB-12 Population in Yogurt Smoothies Throughout Shelf Life

BB-12 Population in Capsule Throughout Shelf Life

45

Values in a row without a common UPPERCASE letter are significantly different, P < 0.05

BB-12 concentration (log10 CFU/cap)Month 0 Month 4 Month 12 Month 14 Month 19

10.4 ± 0.0AB 10.4 ± 0.0A 10.3 ± 0.1AB 10.1 ± 0.2BC 10.0 ± 0.0C

46

Conclusions

• Yogurt smoothies were of comparable composition• BB-12 population declined in yogurt smoothies

throughout shelf life• BB-12 population decreased slower in the PRE than

in the POST intervention• BB-12 remained at the specified dose level in all

interventions






47

Recruiting Participants

48

49

Assessed for eligibility (n=136)

Excluded (n=100)• Did not meet inclusion criteria (n= 41)• Declined to participate (n=0)• Other reasons (n=59)

Randomly allocated to receive interventions, including YS, PRE, POST, or CAP (n=36)• Received allocated intervention (n=29)• Did not receive allocated intervention (n=7)

o Schedule conflict (n=2)o Lost to follow-up (n=1)o Other person reasons (n=4)

Allocation

Randomized (n=36)

Enrollment

Expressed interest (n=203)

50

Analysed (n=28)Excluded from analysis (n=1)

Lost to follow-up (n=0)Discontinued intervention after allocation (n=6)• Pregnancy (n=2)• Diagnosed of Irritable Bowel Syndrome (n=1)• Schedule conflict (n=1)• Other personal reasons (n=2)

Analysis

Follow-Up

Crossover

Crossed over to receive other interventions, including YS, PRE, POST, or CAP (n=29)• Received allocated intervention (n= 29)• Did not receive allocated intervention (n=0)

51

Participant CharacteristicsCharacteristics Values (n = 28)Age (yr) 28.2 ± 0.6Male, n (%) 11 (39.3%)Body mass index (kg/m2) 24.1 ± 0.2

≤24.9 16 (57.1%)25.0 -29.9 11 (39.3%)≥30 1 (3.6%)

Waist Circumference (cm) 85.2 ± 0.6

Blood pressure (mm Hg)Systolic 107.7 ± 0.8Diastolic 72.8 ± 0.6

Glucose (mg/dL) 86.6 ± 0.8Insulin (mg/dL) 5.4 ± 0.4hs-CRP (mg/L) 2.0 ± 0.5Physical activity (METs)2 3.0 (2.3 – 4.3)

52

Methodology – Gut Transit Time• Baseline transit time measured using blue dye and SmartPill

• SmartPill measurement were taken immediately after each intervention period– Gastric Emptying Time (GET)

– Small Bowel Transit Time (SBTT)

– Colonic Transit time (CTT)

– Whole Gut Transit Time (WGTT)

www.givenimaging.com

53

SmartPill Administration

• Fast for 8 hours

• Eat a SmartBar prior to SmartPill ingestion (drink ½ cup blue dye solution at baseline)

• Ingest the capsule

• Nothing to eat for the next 6 hours

• Passed capsule within a few days

• Collect data recorder and download data

• Analyze data using MotiliGI software

54

GET SBTT CTT

Pres

sure

pH

Tem

pera

ture

WGTT

55

Specific Aims 2 & 3 - Results

56

Baseline WGTT as Measured by Blue Dye and SmartPill (ρ = 0.67, P < 0.0001)

0

20

40

60

80

100

120

140

PRO

036

PRO

030

PRO

016

PRO

013

PRO

006

PRO

012

PRO

035

PRO

003

PRO

002

PRO

025

PRO

010

PRO

014

PRO

021

PRO

028

PRO

009

PRO

019

PRO

032

PRO

033

PRO

008

PRO

027

PRO

029

PRO

015

PRO

034

PRO

020

PRO

022

PRO

026

PRO

004

PRO

023

Who

le g

ut tr

ansi

t tim

e (h

)

Participant's ID

SmartPill Blue Dye

57-120

-100

-80

-60

-40

-20

0

20

40

60

80

2 3 4 6 7 8 9 12 13 14 15 16 17 19 20 21 22 24 25 26 28 29 30 32 33 34 35

Tim

e (h

)

Participant ID

YS PRE POST CAP

Changes in Colonic Transit Time (CTT) from Baseline after each Treatment

58

Regional Transit Times (h) of the Participants

WGTT CTT SBTT GET

YS (A) 36.08 ±24.95

27.76 ±24.90

5.40 ±3.40

2.91 ±0.94

POST (B) 35.02 ±17.12

27.51 ±16.26

4.42 ±1.81

3.07 ±1.32

BL 40.78 ±24.50

33.21 ±24.25

4.69 ±1.38

2.86 ±0.89

PRE (C) 38.51 ±26.63

30.80 ±26.21

4.54 ±1.65

3.04 ±1.13

CAP (D) 35.54 ±14.74

27.71 ±14.07

4.40 ±1.46

3.41 ±1.27

Values shown are mean ± SD

59

Conclusions• Blue dye method was proven a generally reliable cost-efficient

method for baseline screening• No significant treatment effect was observed on either gut

transit time or fecal short chain fatty acids• Predominant fecal SCFAs negatively correlated with WGTT,

CTT, and GET, but did not correlate with SBTT





• Aim 4: Assess the influence of consumption of yogurt smoothie (with and without BB-12) and BB-12 containing capsules on participants’ fecal microbiota 60

61

Glossary

• 16S rDNA: The genes coding for 16S ribosomal RNA, a component of the 30S small subunit of prokaryotic ribosomes

• Operational Taxonomic Unit (OTU): A cluster of sequence reads with 97% similarity, motivated by the expectation that these correspond approximately to species

• Alpha-diversity: diversity within a sample

• Beta-diversity: dissimilarity between microbial communities based on their composition (Whittaker 1972, Caporaso et al. 2010)

http://drive5.com/usearch/manual/otu_definition.html

62

Methodology for Microbiota Assessment

• Stool samples were collected at baseline, after each treatment, and after final washout

• Store in a home freezer prior to long-term storage at -80°C at the CRC

• DNA was extracted using MOBIO PowerSoil®

Kit– BAL specific PCR compliance check

– 16S rDNA amplified for V4 region

• Sequenced by Illumina® GAIIx

• Data processed using QIIME

– Bif-TRFLP

63

DNA extraction

Stool DNA

PCR Compliance

checkBif-TRFLP

Amplify V4 region of 16S

rDNA

Barcode

Verify amplicons

Purify and combineSequence

Data Demultiplex and QA data Pick OTUs

OTU table

α-diversity β-diversity

Phylogenetic tree

LEfSe

QIIME

Experimental Procedure and Data Analysis

64

Specific Aim 4 - Results

65

Compliance Result• 73/78 fecal samples were BAL positive after receiving

BB-12 interventions

• All samples were BAL negative after receiving control yogurt smoothie when the corresponding baselines were negative

• Samples from 5 individuals were BAL positive regardless of treatment

66

Alpha Rarefaction Curves of the Sequences

67

Compositional Characteristics of the Fecal Microbiota of Participants

Compositional Characteristics of the Fecal Microbiota of the Participants

68

69

Simpson α-Diversity Index of the Fecal Microbiota of the Participants Before and After each Treatment

70

Weighted UniFrac Distance PCoA of the Fecal Microbiota Group by Treatment

71

Weighted UniFrac Distance PCoA of the Fecal Microbiota Group by Gender

72

Unweighted Pair Group Method with Arithmetic mean (UPGMA) Tree Based on Weighted UniFracDistanceDemonstrating the Hierarchical Relationships Between Fecal Samples

73

Relative Proportion of Bifidobacterium Species in the Stool Samples as Determined by Bif-TRFLP

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Baseline YS (A) POST (B) PRE (C) CAP (D) FinalWashout

Rel

ativ

e pr

opor

tion

Treatment

B. adolescentisB. animalisB. breveB. bifidum/pseudocatB. longumB. pseudocatenulatumUnknown

74

Conclusions

• No significant treatment effect on gut microbiota was detected although yogurt interventions tended to exhibit a higher abundance of Streptococcus

• A significant gender effect was observed when comparing the gut microbiota of present study cohort

• BB-12 containing yogurt smoothies resulted in higher relative abundance of B. animalis

75

Overall Conclusions

• Consumption of BB-12 delivered in yogurt or capsule did not change the gut transit time, fecal short chain fatty acid concentration, or the composition of the gut microbiota of the study cohort.

• Daily consumption of BB-12 in yogurt smoothie for 4 weeks may have an anti-inflammatory effect (data not shown) and result in higher relative abundance of B. animalis than capsule, control yogurt smoothie, baseline, and final washout.

76

Acknowledgements

• DMI/DRI for Research Support

• Dr. Byron Ba• Dr. Rodolphe Barrangou

• Dr. Ryan Elias

• Dr. Penny Kris-Etherton

• Dr. James Rosenberger

• Berkey Creamery Staff

• Dr. Emily Furumoto

• Dr. Connie Rogers

• Jennifer Fleming

• Dr. Huicui Meng

• Yujin Lee

• Dr. David Mills

• Dr. Zac Lewis

• Morgan Bennett

• PSU Clinical Research Center

• Volunteers

Thank you for your attention!Questions?

77

Documents

DRI Project Report - Ice Cream Mix - Roberts Dairy Research... · National Ice Cream Mix Association ... • Global probiotic market is projected to reach $46.55 ... (Human Microbiome