probiotic bacteria survive in cheddar cheese and modify populations of other lactic acid bacteria

ORIGINAL ARTICLE

Probiotic bacteria survive in Cheddar cheese and modifypopulations of other lactic acid bacteriaB. Ganesan1,2, B.C. Weimer3, J. Pinzon3, N. Dao Kong3, G. Rompato4, C. Brothersen1,2 andD.J. McMahon1,2

1 Dairy Technology and Innovation Laboratory, Western Dairy Center, Utah State University, Logan, UT, USA

2 Department of Nutrition, Dietetics, and Food Sciences, Utah State University, Logan, UT, USA

3 Department of Population Health and Reproduction, University of California, Davis, CA, USA

4 Center for Integrated BioSystems, Utah State University, Logan, UT, USA

Keywords

Cheddar cheese, low fat, nonculturability,

probiotic, survival.

Correspondence

Balasubramanian Ganesan, Dairy Technology

and Innovation Laboratory, Western Dairy

Center, Utah State University, 8700 Old Main

Hill, Logan, UT 84322, USA.

E-mail: [email protected]; and

Bart C. Weimer, University of California,

Davis School of Veterinary Medicine 1089

Veterinary Medicine Dr. VM3B, Room 4023

Davis, CA 95616, USA.

E-mail: [email protected]

2013/2047: received 8 October 2013, revised

6 January 2014 and accepted 12 February

2014

doi:10.1111/jam.12482

Abstract

Aims: Starter lactic acid bacteria in Cheddar cheese face physico-chemical

stresses during manufacture and ageing that alter their abilities to survive and

to interact with other bacterial populations. Nonstarter bacteria are derived

from milk handling, cheese equipment and human contact during

manufacture. Probiotic bacteria are added to foods for human health benefits

that also encounter physiological stresses and microbial competition that may

mitigate their survival during ageing. We added probiotic Lactobacillus

acidophilus, Lactobacillus casei, Lactobacillus paracasei and Bifidobacterium

animalis subsp. lactis to full-fat, reduced-fat and low-fat Cheddar cheeses,

aiming to study their survival over 270 days of ageing and to determine the

role of the cheese matrix in their survival.

Methods and Results: Probiotic and other lactic acid bacterial populations

were enumerated by quantitative PCR using primers specifically targeting the

different bacterial genera or species of interest. Bifidobacteria were initially

added at 106 CFU g�1 cheese and survived variably in the different cheeses

over the 270-day ageing process. Probiotic lactobacilli that were added at

107 CFU g�1 cheese and incident nonstarter lactobacilli (initially at 108 CFU

g�1 cheese) increased by 10- to 100-fold over 270 days. Viable bacterial

populations were differentiated using propidium monoazide followed by

species-specific qPCR assays, which demonstrated that the starter and probiotic

microbes survived over ageing, independent of cheese type. Addition of

probiotic bacteria, at levels 100-fold below that of starter bacteria, modified

starter and nonstarter bacterial levels.

Conclusions: We demonstrated that starter lactococci, nonstarter lactobacilli

and probiotic bacteria are capable of surviving throughout the cheesemaking and

ageing process, indicating that delivery via hard cheeses is possible. Probiotic

addition at lower levels may also alter starter and nonstarter bacterial survival.

Significance and Impact of the Study: We applied qPCR to study multispecies

survival and viability and distinctly enumerated bacterial species in

commercial-scale Cheddar cheese manufacture.

Introduction

Probiotic bacteria are defined as ‘live micro-organisms

which when administered in adequate amounts confer a

health benefit on the host’ (FAO/WHO 2002; Morelli and

Capurso 2012). The consumption of probiotic bacteria is

reported to confer many health benefits such as prevent-

ing gut inflammation, immunomodulation, preventing

Journal of Applied Microbiology 116, 1642--1656 © 2014 The Society for Applied Microbiology1642

Journal of Applied Microbiology ISSN 1364-5072

food allergy and also potentially provide anticarcinogenic

activity (Kailasapathy 2002; Caglar et al. 2005; Mengheri

2008). As early as infancy, probiotic bacterial species that

are components of the native microbiota of breast milk

enter the human colon. Probiotic bacteria are also sup-

plemented via infant formula (Moreno Villares 2008; de

Vrese and Schrezenmeir 2008) to aid milk oligosaccharide

digestion (Macfarlane et al. 2008), whereas adults typi-

cally source probiotics from fermented milks and nutri-

tional supplements. The consumption of probiotic-

supplemented cheese boosts innate immunity of geriatric

patients (Ibrahim et al. 2010). However, probiotic bacte-

ria must survive in foods to reach the human gastrointes-

tinal system and to further modify gut microbiota

(Kramer et al. 2009; Yu et al. 2009). Guidelines for pro-

biotic bacteria recommend that identity at the species

level must be established (FAO/WHO 2002).

Probiotic bacteria such as Bifidobacterium longum,

Bif. lactis, Lactobacillus acidophilus, Lact. casei and

Lact. paracasei are usually added to yoghurt and other

fermented milks (Heller 2001), and more recently to

cheese (Gardiner et al. 1998) as delivery vehicles for

human consumption. Lactococcus lactis is used as a starter

culture to produce lactic acid for pH reduction during

Cheddar cheese manufacture, whereas nonstarter lactic

acid bacteria (NSLAB) and other microbes are either

present in cheese milk or are added purposefully (Peter-

son and Marshall 1990; Trepanier et al. 1991; Habibi-

Najafi and Lee 1996; Swearingen et al. 2001). Probiotic

bacteria are usually added to cheese milk and thus

sequentially undergo physico-chemical stresses such as

heat, acid, salt and cold during initial manufacture, as

well as changes in redox potential over storage and distri-

bution (Rallu et al. 1996; van de Guchte et al. 2002), as

do other adventitious or added lactic acid bacteria (LAB).

When cheeses are manufactured from milk of different

fat contents (Bertoni et al. 2001), the sequence of abiotic

stresses varies due to the different processing conditions

used (Fox and Wallace 1997; Banks 2007; Coolbear et al.

2011), which may alter subsequent LAB survival during

ageing. As NSLAB survive in cheese and grow over age-

ing, of which lactobacilli are the dominant species, probi-

otic lactobacilli species may also remain viable in

Cheddar cheese during ageing until consumption to pro-

vide health benefits.

Estimates of bacterial viability in different foods and

environments vary based on the enumeration techniques

used. Growth media-based enumeration discounts possi-

ble alternate physiological states of bacteria, such as non-

culturability (Fenelon et al. 2000; Ganesan et al. 2007).

Such growth-based observations led to a previous

hypothesis that starter bacteria die and lyse to subse-

quently provide substrates that accelerate NSLAB growth

(Branen and Keenan 1969; Crow et al. 1995; Buist et al.

1997, 1998). However, lactococci, NSLAB and brevibacte-

ria become nonculturable in carbohydrate-depleted media

while remaining metabolically active (Ganesan et al.

2004, 2007) and maintain substrate transport for produc-

ing energy from alternate substrates (Ganesan et al.

2007). The declining lactococcal counts in cheese may

represent a subpopulation of replicating cells, while a

nonculturable population of cells that is unable to divide

and is hence not enumerated on growth media (Kilcawley

et al. 2011) coexists. Additionally, the enumeration of an

entire genus using selective growth media does not accu-

rately reflect the metabolic contributions of multiple spe-

cies of a diverse genus, such as Lactobacillus (Peterson

and Marshall 1990; Trepanier et al. 1991), that shares

metabolic capabilities with other Lactobacillales (Makar-

ova et al. 2006). Hence, alternate population assessment

methods are needed to better estimate LAB species diver-

sity in cheese and survival of probiotic bacterial species

in foods used for delivery.

Multiple studies at laboratory- or pilot-scale cheese

manufacture have demonstrated probiotic bacterial sur-

vival in hard cheeses such as Cheddar, a representative

set of which are listed in Table 1. According to these

studies, even the same strains or species survive variably,

with one group showing survival throughout ageing, but

another demonstrating loss of viability of the same in 6–8 weeks. Some studies were conducted in smaller scale

(10–20 l of milk), which do not represent issues in com-

mercial-scale manufacture such as adventitious NSLAB

and bacteriophages’ presence. Notably, none of these

studies enumerated survival of probiotic bacteria at the

species level. Neither did these studies assess the impact

of adding a microbe not usually found in cheese on the

starter or NSLAB of cheeses. In one study that used

qPCR for detecting bacteria (Achilleos and Berthier

2013), only soft cheeses were assessed over 24 h and did

not address the challenge of detecting bacteria in aged

semi-hard cheeses.

To meet regulatory requirements, bacteria are isolated

from foods (Giraffa and Rossetti 2004; Rossetti and Giraf-

fa 2005) prior to species identification based on 16S or

23S rRNA genes using organism-specific primers (Salama

et al. 1991; Klijn et al. 1995), single-gene sequencing, ran-

dom DNA amplification, use of restriction enzyme diges-

tion patterns (Byun et al. 2004; Rossetti and Giraffa

2005), gel electrophoresis by varying electric fields (pulse

field) (Klein et al. 1998; Henri-Dubernet et al. 2008), tem-

perature (Vasquez et al. 2001; Ogier et al. 2002) or chemi-

cal gradients (denaturing gradient) (Fasoli et al. 2003);

however, these methods do not enumerate bacteria nor

conclusively establish species identity. With advances in

PCR amplification technology and the use of fluorescent

Journal of Applied Microbiology 116, 1642--1656 © 2014 The Society for Applied Microbiology 1643

B. Ganesan et al. LAB survival in probiotic-added cheese

Table

1Previousstudiesofprobioticad

ditionto

Ched

dar

cheese

Study

Probioticbacteriaused

Scaleof

cheese

man

ufacture

Targeted

levelof

probiotics

(CFU

g�1)

Detectionmethodin

cheese

Viability

assessmen

tin

cheese

Detectedlevels

ofprobiotics

(CFU

g�1)

Cheese

ageing

period

(months)

Detection

limitsof

assays

(CFU

g�1)

Dinakar

and

Mistry(1994)

Bifidobacterium

bifidum

(immobilized;ad

ded

duringsalting)

100kg

106

Microbialplatingonselectivemed

iaMicrobialplatingonselectivemed

ia106to

107

625

Gardiner

etal.(1998)

Lactobacillussalivarius,

Lact.paracasei

25,450l

(2reps9

2strains

only)

NS

RAPD

-PCR/gel

electrophoresison

DNAextractedfrom

growncolonies


ia108

825

Daigle

etal.(1999)

Bifidobacterium

infantis

250l

59

107



ia107

325

Gardiner

etal.(1999a)

Enterococcusfaecium

450l

49

108

Antibioticresistan

cemutant


ia49

108

15

25

Gardiner

etal.(1999b)

Ent.faecium

450l

108

Antibioticresistan

cemutant


ia39

108

925

McBrearty

etal.(2001)

Bif.sp.

450l

108

RAPD

-PCR/gel

electrophoresison

DNAextractedfrom

growncolonies


ia105to

108

625

Auty

etal.(2001)

Lact.paracasei,

Bif.sp.BB-12

450l

108


ia,

stainingan

dconfocalmicroscopy


ia,

stainingan

dconfocalmicroscopy

NS

108(confocal)

Phillips

etal.(2006)

Lactobacillusacidophilus,

Bifidobacterium

sp.,Lact.casei,

Lact.paracasei

andLact.rham

nosus

10l

108



ia103to

108

925

Sharp

etal.(2008)

Lact.casei

136kg

107

Antibioticresistan

cemutant


ia107

325

Ongan

dSh

ah

(2008)

Lact.acidophilusan

d

Lact.helveticus

20l

NS



ia108

625

Achilleo

san

d

Berthier(2013)

Lact.paracasei

Not

disclosed

108

Microbialplatingonselective

med

iaan

dqPC

R

Microbialplatingonselective

med

iaan

dqPC

R

108

0200

NS,

notspecified

.


LAB survival in probiotic-added cheese B. Ganesan et al.

labelling, reliable estimates of bacterial populations for a

single genus or species are easily obtained using quantita-

tive PCR (qPCR) (Matsuki et al. 2004; Kramer et al.

2009). Recent studies have established the applicability of

this technology to other fermented dairy products such as

yoghurt (Fasoli et al. 2003; Rademaker et al. 2006; Sieuw-

erts et al. 2008; Garcia-Cayuela et al. 2009; Sheu et al.

2009), and its applicability to cheese has been demon-

strated.

Nucleic acid extraction directly from a food matrix was

previously limited by high carbohydrate, protein and

lipid contents, but methods are now available to extract

high-quality DNA for direct use in identification strate-

gies. Challenges in direct nucleic acid extraction from

cheese were previously circumvented by prior microbial

cell separation from the cheese matrix for nucleic acid

extraction (Rudi et al. 2005; Fernandez et al. 2006; Mon-

net et al. 2006; Fukushima et al. 2007) or using large

sample quantities (≥10 g cheese) (Monnet et al. 2006,

2008; Sohier et al. 2012). Else, the methods only provided

higher detection limits (≥1000 CFU g�1) (Baruzzi et al.

2005; Rantsiou et al. 2008; Sheu et al. 2009) or are inca-

pable of distinguishing added probiotic lactobacilli from

NSLAB lactobacilli (Gardiner et al. 1998). Such

approaches cannot determine changes of species levels in

long-term aged cheeses. However, using genus- and spe-

cies-specific qPCR, population changes of distinct groups

of LAB specifically induced by probiotic addition can be

determined.

We hypothesized that the addition of specific probiotic

bacteria to cheese during manufacture modifies starter

and NSLAB lactobacilli survival in Cheddar cheese at dif-

ferent fat levels. In this study, three cheese types that had

different fat contents were made to determine the role of

the physico-chemical conditions in such cheeses in allow-

ing survival of probiotic lactobacilli and bifidobacteria by

applying a qPCR-based bacterial detection method. We

also assessed whether addition of probiotics at levels

below that of starter bacteria altered starter or NSLAB

levels. Further, the viability of the three groups of bacte-

ria was also determined using propidium iodide-based

qPCR assays. DNA extraction from small quantities of

cheese (0�2–1 g) was optimized by coupling physico-

chemical and enzymatic lysis of bacteria to release nucleic

acids, followed by phenol–chloroform-based applications

to remove protein and lipid. We found that starter,

NSLAB lactobacilli and probiotic bacteria survive

throughout Cheddar cheese ageing with limited reduction

in viability and that probiotic addition even at levels

lower than starter LAB, altered levels of starter lactococci

and NSLAB lactobacilli.

Materials and methods

Probiotic-added cheese manufacture

Starter culture, probiotic adjunct, suppliers and the

amount of culture used are indicated in Table 2. The tar-

geted range of probiotic bacteria in the finished cheese

was 3�6 9 106–107 CFU g�1 (based on the requirement

of ≥108 CFU per 28 g serving), and direct-vat-set cultures

were added proportionally based on manufacturer’s speci-

fications and expected cheese yields to achieve the target

levels. The control cheese was made with Lc. lactis

DVS850 starter culture only, while the probiotic cheeses

each contained DVS850 and one probiotic culture.

Table 2 Starter culture, probiotic adjunct, suppliers and the amount of freeze-dried culture used

Supplier Organism Name

Amount used in cheese (g)*

Full fat (160 kg

cheese milk)

Reduced fat (135 kg

cheese milk)

Low fat (135 kg

cheese milk)

Chr. Hansen, Milwaukee,

WI, USA

Lactococcus lactis DVS850 17�0 30�0 26�0

Cargill Inc., Waukeshaw,

WI, USA

Bifidobacterium lactis Bif-6 14�0 12�0 12�0

Chr. Hansen Bif. lactis BB-12 14�0 12�0 12�0Chr. Hansen Lactobacillus acidophilus LA-5 14�0 12�0 12�0DSM Food Specialties,

Logan, UT, USA

Lact. acidophilus L10 7�8 6�7 6�7

DSM Food Specialties Lactobacillus casei L26 6�4 5�5 5�5Chr. Hansen Lact. casei CRL-431 14�0 12�0 12�0Chr. Hansen Lactobacillus paracasei

subsp. paracasei

F19 35�0 30�0 30�0

*Inoculation levels were adjusted by milk quantity and manufacturer-provided information about cultures on numbers of viable bacteria in

freeze-dried cultures to achieve the desired target ranges of 107 to 108 CFU g�1 probiotic bacteria in cheese.



Manufacturing procedures for full-fat, reduced-fat and

low-fat Cheddar cheeses are described in the supplemen-

tary materials and methods section, along with proximate

analysis procedures for cheese.

Sampling

After ageing for 5 days, the cheese was cut into 10 blocks

of c. 1 kg each, vacuum packaged and stored at 3°C. Foreach replicate treatment, one block was randomly chosen

for analysis at 5 days, 1, 2, 3, 4, 6 and 9 month of age.

Extraction of genomic DNA from cheese

To extract DNA from all three types of cheese, finely

grated cheese (0�25 g) was suspended in TrizolLS (500 ll;Invitrogen, Carlsbad, CA, USA) along with glass beads

(0�3 g, size 0�1 mm; sterile, acid-washed; BioSpec Prod-

ucts Inc., Bartlesville, OK, USA). The cheese-TrizolLS sus-

pension was disrupted on a Mini-Beadbeater (BioSpec

Products) for 30 s to lyse bacteria and further shaken

with chloroform (200 ll) for 30 s to allow phase separa-

tion. The top aqueous phase was removed after centrifu-

gation (12 000 g for 15 min at room temperature), and

DNA was precipitated from the lower organic phase with

100% ethanol for 3 min. DNA was collected by centrifu-

gation (2000 g for 5 min at 4°C), washed twice with

0�1 mol l�1 sodium citrate in 10% ethanol (30 min at

room temperature), once with 75% ethanol (15 min at

room temperature), pelleted, air-dried and resuspended

in sterile double-deionized water (ddH2O) This DNA was

used to measure population changes of lactobacilli and

bifidobacteria.

Due to poor efficacy of glass bead lysis for lactococcal

detection (Fig. S2), lactococcal lysis was separately

accomplished by an enzymatic approach in which finely

grated cheese (0�25 g) was treated with bacterial lytic

enzymes (initially 50 mg ml�1 lysozyme + 10 U ml�1

mutanolysin at 37°C for 1 h, followed by 9 U ml�1

proteinase K at 50°C for 1 h). This was followed by phe-

nol–chloroform extraction of DNA and qPCR for enu-

merating lactococci using genus-specific primers. This

lysis approach was also applied to cheeses tested for via-

ble bacterial levels (see below).

DNA quality and yield

DNA quality and yield were checked on a Nanodrop

spectrophotometer (Agilent Technologies, Santa Clara,

CA, USA). All samples used in qPCR had a A260/A280

ratio ≥1�8.

Quantitative PCR

Bacterial levels in cheese were determined by qPCR in

triplicate reactions. Compliance to MIQE guidelines was

ensured throughout the process of qPCR analyses, data

extraction and data analysis (Table S5). All bacterial

primers were selected from previous studies that designed

genus- and species-specific primers for the starter and

probiotic organisms (Table 3) and were subsequently val-

idated by assays against the strains used in this study

prior to use (see Fig. S1). Briefly, the total DNA extracted

from cheese was used in a 25-ll reaction that included

qPCR master Mix (HotStart-IT� SYBR� Green; USB

Corp., Cleveland, OH, USA) and genus- and species-spe-

cific primers targeting the 16s rRNA gene (Table 3). Each

final reaction mixture contained: template DNA, 500 ng,

MgCl2, 2�5 mmol l�1, primers, 10 pmol and each dNTP,

0�4 mmol l�1. The qPCR was performed on a DNA

Engine OPTICON2 (Bio-Rad Labs Inc., Hercules, CA,

USA) with initial enzyme activation at 95°C for 5 min,

followed by 40 cycles of: denaturation at 95°C for 15 s,

annealing at 50°C for 30 s and extension at 72°C for

1 min. All DNA samples from probiotic-added cheeses

were always assayed simultaneously with DNA samples

from control cheeses (no probiotic added) using species-

specific primers to confirm lack of amplification. Following

Table 3 Sequences of primers used for genus- or species-specific 16s ribosomal gene qPCR for different cheese bacteria

Organism Specificity Primer sequence Cheeses applied to References

Lactococcus lactis Genus F: 50- GCGGCGTGGCTAATACATGC-30

R: 50- CTGCTGCGTCCCGTAGGAGT-30All Klijn et al. (1995)

Bifidobacterium lactis Species F: 50-GTGGAGACACGTTTCCC-30

R: 50-CACACACACAATCAATAC-30Bif-6, BB-12 Ventura et al. (2001)

Lactobacillus Genus F: 50-TGGAAACAGRTGCTAATACCG-30

R: 50-GTCCATTGTGGAAGATTCCC-30Control, LA-5, L10, L26, F19 Byun et al. (2004)

Lactobacillus acidophilus Species F: 50-GAGGCAGCAGTAGGGAATCTTC-30

R: 50-GGCCAGTTACTACCTCTATCCTTCTTC-30LA-5, L10 Delroisse et al. (2008)

Lactobacillus casei/paracasei Species F: 50-GCACCGAGATTCAACATGG-30

R: 50-GGTTCTTGGATYTATGCGGTATTAG-30L26, F19 Byun et al. (2004)



MIQE-compliant procedures, results from all qPCR

assays were extracted using OPTICON monitor software

v2.2 (Bio-Rad).

Viable bacterial qPCR assay using propidium monoazide

The viability of bacteria present in cheese was verified by

a qPCR-based assay, using the DNA-chelating reagent

propidium monoazide (PMA; Biotium Inc., Hayward,

CA, USA). Briefly, the assay was conducted as follows: a

small portion of cheese (0�25 g) was thoroughly minced,

suspended in an equal amount (w/v) of sterile ddH2O,

and a stock of 20 mmol l�1 PMA was added to the

cheese suspension to obtain a final concentration of

50 lmol l�1, as described by Nocker et al. (2007). The

addition and mixing was carried out in light-transparent

tubes that were then kept in dark for 10 min to allow

PMA-nucleic acid binding, followed by exposure to a

650 W halogen lamp for 5 min, with samples kept on

ice, to quench the reaction. After light exposure, samples

were treated with lysozyme–mutanolysin and DNA was

extracted for qPCR-based enumeration. For live-dead

assays by qPCR using PMA, the difference in Cq times

with and without PMA addition, denoted as DCq, wasmonitored over cheese age.

Statistical analysis

All cheeses were made in two replicates that were manu-

factured from different batches of milk. Cheese samples

were collected for qPCR enumeration at 5 days, 1, 2, 3,

4, 6 and 9 months. Each sample was analysed by qPCR

in triplicate, and the results of bacterial counts from

qPCR assays were analysed as a nested factorial repeated-

measures design (Ganesan et al. 2007) to understand the

impact of cheese type on survival of different added pro-

biotics and the impact of cheese type and strain on sur-

vival of NSLAB. JMP v7 statistical software (The SAS

Institute, Cary, NC, USA) was used for repeated-mea-

sures statistical analyses. For the time series analyses, sig-

nificance was assigned at a = 0�05/n, where n is the

number of time points. Two-sample statistical compari-

sons within a particular condition when necessary were

performed by two-tailed Student’s t-tests with Microsoft

Excel software (Redmond, CA, USA), and significance

was assigned at a = 0�05.

Results

LAB population changes during ageing

Three types of Cheddar cheeses—full, reduced and low

fat—were manufactured (Table S1), and seven probiotic

bacterial species were added to the different cheeses.

Changes in specific LAB populations over ageing were

assessed by qPCR using a species primer set that corre-

sponded to the species added to the cheeses (validation

and variability results in supplementary material). We

developed a sensitive qPCR assay based on previously val-

idated primers that provided reliable detection even at

10–500 CFU g�1 from Cheddar cheese (Table S2). The

targeted levels of probiotics in cheese were at least

10 000-fold higher than our detection limits.

Primarily, probiotic bacteria were added targeting a

final level of 3�6 9 106–107 CFU g�1 cheese, which was

accomplished in all full- and low-fat cheeses (Fig. S3).

Interestingly, added probiotic lactobacilli populations

were consistently lower than the target level by 10-fold

initially in reduced-fat Cheddar cheeses, but rose to attain

levels of c. 107–108 CFU g�1 cheese within a month of

ageing (Fig. S2), indicating that they grew in the cheese

by 10- to 100-fold. However, at any time, probiotic lacto-

bacilli levels were only 1–10% of that of total lactobacilli

(Figs S2 and S4), confirming that added probiotic and

NSLAB lactobacilli can be distinctly enumerated using

qPCR.

Probiotic Lact. casei/paracasei survived through

270 days of ageing in all Cheddar cheeses either at com-

parable levels or grew by 10- to 70-fold (Table 4), with

differences in final levels attained within each fat level

(P ≤ 0�05). Added Lact. acidophilus exhibited a 16- to 37-

fold reduction in population (P ≤ 0�05) from the initial

level of addition during ageing in low-fat cheese

(Table 4). However, Lact. acidophilus strains did not dif-

fer in survival patterns over time across the different fat

Table 4 Fold change of different probiotic bacterial populations in

cheeses over 270 days of ageing

Probiotic organism

Fold change in populations (CFU g�1 ratio of

270 days/0 days)*

Full fat Reduced fat Low fat

Lactobacillus

acidophilus LA-5

�1�9 � 2�3 13 � 0�9 �16 � 0�4

Lact. acidophilus L10 2�3 � 1�0 230 � 0�9 �37 � 1�4Lactobacillus

casei CRL-431

4�1 � 2�0 9�3 � 0�9 71 � 0�6

Lact. casei L26 16 � 0�4 7�4 � 0�2 3�5 � 0�3Lactobacillus

paracasei F19

1�5 � 0�5 2�2 � 1�0 5�2 � 0�8

Bifidobacterium

lactis Bif-6

�12 � 10 2�8 � 1�1 �6900 � 10

Bif. lactis BB-12 �3200 � 100 1500 � 10 �2�7 � 1�0

Negative sign indicates reduction.

*Values are indicated followed by standard deviations after the ‘�’

sign.



levels (P > 0�05). In contrast, Bif. lactis strains exhibited

varying survival patterns (P ≤ 0�05) within each fat level,

with the Bif-6 strain populations declining by 6900-fold

in low-fat cheese within 270 days, whereas the BB-12

strain declined by 3200-fold in full-fat cheese (Table 4).

Bif-6 remained at similar levels to initial inoculum in

reduced-fat cheese (P > 0�05), whereas BB-12 increased

by 1500-fold (P ≤ 0�05) (Table 4). Notably, estimates of

bifidobacterial levels varied by 100- to 1000-fold within

replicates for 43% of cheeses across age and fat level,

which precluded any strong conclusions about their pop-

ulation variations. Such variation was much less prevalent

in probiotic lactobacilli (9% cheeses with 100- to 1000-

fold variation). However, bifidobacteria were exclusively

detected by qPCR throughout cheese ageing, which con-

firms their viability in cheese.

To understand the role of cheese fat content on micro-

bial survival, we directly compared the probiotic levels in

reduced-fat and low-fat cheeses. Interestingly, the lower

fat level appeared to reduce bacterial survival, as high-

lighted by significant decrease (P ≤ 0�05) in numbers of

Lact. acidophilus over ageing in low-fat cheese. However,

Lact. casei/paracasei grew in both reduced- and low-fat

cheeses. These results indicated that fat in cheese may aid

survival of selected species of lactobacilli during ageing.

As probiotic bacteria were added at levels of 107 CFU

g�1 and survived variably, they may alter the levels of

starter LAB and NSLAB in ageing Cheddar cheese. We

assessed the effect of probiotic addition by measuring

changes in overall lactobacilli populations using a primer

set targeting the Lactobacillus genus. Notably, in all

cheeses tested, levels of total lactobacilli were 10- to 100-

fold higher than levels of added probiotic, and the pat-

terns of survival of these two groups were different

(P ≤ 0�05) (Figs S2 and S4). However, survival and

growth of total lactobacilli in the probiotic lactobacilli-

added cheeses differed due to the different strains added

and fat level (P ≤ 0�05). While the overall populations of

total lactobacilli remained at 108 CFU g�1 or higher in

all cheeses, the addition of Lact. acidophilus La-5 and

Lact. casei CRL431 significantly (P ≤ 0�05) altered the

levels of total lactobacilli, dependent on cheese fat level.

For example, at 270 days of ageing, La-5 addition

reduced total lactobacilli by eightfold in the reduced-fat

cheese, but there was no change in the low-fat cheese

(P ≤ 0�05; Table 5). Addition of CRL431 decreased total

lactobacilli by sevenfold in reduced-fat Cheddar cheese

and increased total lactobacilli by sevenfold in low-fat

cheese (P ≤ 0�05; Table 5). Addition of other probiotic

organisms did not alter total lactobacilli levels (P > 0�05),but cheese fat level altered (P ≤ 0�05) the total lactobacilli

levels. One such example is the cheeses to which Lact. pa-

racasei F19 was added, in which total lactobacilli levels

had increased 34-fold in 270-day-old low-fat cheese

(P ≤ 0�05), but had decreased sixfold in reduced-fat

cheese (Table 5). These results indicate that fat reduction

in cheeses and probiotic addition alters survival of

NSLAB lactobacilli over cheese ageing.

As NSLAB levels were altered by addition of probiotic

lactobacilli and bifidobacteria, we also measured changes

in lactococcal populations using PCR targeting Lc. lactis

species in all three cheese types in a limited set of sam-

ples. Lactococcal populations in the control (no probiotic

added) cheeses were compared to levels in Lact. acidophi-

lus L-10-added and Bif. lactis Bif-6-added cheeses. Lacto-

coccal counts in control cheeses ranged between

7�5 9 107 and 8 9 108 CFU g�1 and did not change

over time. Addition of different probiotics significantly

(P ≤ 0�05) altered lactococcal populations and also the

effects varying within each fat level. For example, addi-

tion of Bif-6 did not change lactococcal levels within

270 days in low-fat cheeses, but decreased lactococcal

populations in reduced-fat cheeses by 10-fold compared

to without Bif-6 addition (P ≤ 0�05; Fig. 1), whereas L-10addition consistently allowed lactococci to survive at 10-

to 100-fold higher levels than without probiotic addition

in low-fat cheeses (P ≤ 0�05), but did not alter lactococ-

cal levels in reduced- and full-fat cheeses.

Viability of LAB in cheese

LAB that do not survive the harsh cheese conditions may

die, and their cell walls and membranes may rupture,

releasing DNA and intracellular contents into the cheese

matrix where it may remain stable and be detected using

PCR, which could artificially elevate the bacterial esti-

mates during qPCR assays. Such extracellular DNA can

be removed by treating samples with DNase enzyme prior

Table 5 Fold change of total lactobacilli populations in cheeses

added with different probiotic lactobacilli over 270 days of ageing

Probiotic organism

Fold change in populations (CFU g�1

ratio of 270 days/0 days)*

Full fat

(n = 2)

Reduced fat

(n = 2)

Low fat

(n = 2)

Lactobacillus

acidophilus LA-5

�1�6 � 2�7 �8�1 � 1�3 1�4 � 0�4

Lact. acidophilus L10 3�5 � 0�7 �8�3 � 1�0 �6�0 � 1�6Lactobacillus

casei CRL-431

1�6 � 0�8 �6�9 � 0�7 6�9 � 0�7

Lact. casei L26 5�8 � 0�5 1�7 � 0�2 1�5 � 0�4Lactobacillus paracasei F19 1�6 � 0�4 �5�6 � 0�7 34�2 � 1�3

Negative sign indicates reduction.

*Values are indicated followed by standard deviations after the ‘�’

sign.



to cellular lysis to degrade prereleased DNA. However,

DNase-treated 3-month-old cheeses containing added

Lact. casei L26 and Bif. lactis Bif-6, when tested by qPCR

detection using species-specific primers, did not differ

(P > 0�05) in qPCR Cq times from nontreated cheeses

(Fig. 2), indicating that extracellular DNA was not avail-

able for PCR detection and did not contribute to the

total count using qPCR. This indicated that qPCR assays

are exclusively based on DNA from live bacteria (includ-

ing bacteria that are nonculturable) and that DNA from

dead bacteria is not being enumerated.

Secondarily, bacterial cells may exist in a physiologi-

cally dead state wherein they are partially autolysed or

their cell walls or membranes are partly compromised to

create a leaky membrane, but still contain intact DNA

that could be co-extracted along with live cells’ DNA and

cause overestimation. To assess this potential interference,

we conducted qPCR assays on all three cheese types at

5 days, 4, 6 and 9 months age, to which PMA, a DNA-

chelating dye, was added prior to DNA extraction. PMA

selectively permeates across and binds DNA in dead/com-

promised cells and thus limits PCR amplification from

the chelated DNA, which consequently will increase the

DCq over ageing if cell membrane is compromised. The

procedure of PMA treatment for cheese was validated by

adding 107–108 logarithmic growth phase cells to a cheese

sample obtained from another source prior to PMA treat-

ment, and DNA extraction was followed by qPCR enu-

meration. With and without PMA treatment, the DCqbetween samples was similar (P > 0�05), which proved

that the added cells were live (data not shown). We con-

ducted qPCR assays targeting the starter lactococci in

cheese without added probiotics and two cheeses with

5

6

7

8

9

10

CF

U g

m–1

CF

U g

m–1

CF

U g

m–1

5

6

7

8

9

10

0 90 270Days

5

6

7

8

9

10

120

0 90 270Days

120

0 90 270Days

120

Figure 1 Lactococcal starter bacteria population levels in Cheddar

cheeses estimated by qPCR. Vertical error bars represent standard

deviations of log10 (CFU g�1) assessed from two replicates of cheese.

Top panel, full-fat cheese, middle panel, reduced-fat cheese, and bot-

tom panel, low-fat cheese. (●) Control—probiotic not added; (■) pro-biotic Bifidobacterium lactis Bif-6 added; (♦) probiotic Lactobacillus

acidophilus L10 added.

0

5

10

15

20

25

Genus Species

Cq

Lactobacillus primer type

Figure 2 Quantitative PCR Cq times of Lactobacillus genus and spe-

cies determined from cheeses treated with DNase enzyme prior to

bacterial lysis to remove extracellular DNA. Cheese age was 3 months

and contained added probiotic Lactobacillus casei L26. White bar, no

DNase treatment, grey bar, DNase treated prior to lysis and DNA

extraction.



different probiotic species (Lact. acidophilus La-5 and

Bif. lactis Bif-6) in full-, reduced- and low-fat cheeses

over 9 months of cheese ageing. In almost all cases, the

DCq did not change significantly (P > 0�05) over cheese

age for lactococci (Fig. 3a), suggesting that over ageing

up to 9 months, starter lactococci survive the ageing pro-

cess without loss in viability no change in the membrane

permeability, despite declines in plate counts as demon-

strated by other studies (Crow et al. 1995; Buist et al.

1998; Oberg et al. 2011). The DCq for lactococci did,

however, increase slightly in the low-fat cheese with

added bifidobacteria between 0 and 120 days (Fig. 3a)

and remained at similar levels up to 270 days, suggesting

that the membrane permeation increase was insignificant

over long-term ageing of cheese. Lactococci survived even

after probiotic addition without loss in viability, suggest-

ing that the impact of added probiotics is likely minimal.

This approach also verified that LAB levels assessed by

qPCR identified viable and intact cells that were present

in the cheese matrix and not dead or compromised cells.

Assessing probiotic survival using the PMA-added

cheese samples showed that added lactobacilli also sur-

vived in Cheddar cheese over age, demonstrated by either

a significant reduction in DCq (P ≤ 0�05, full-fat cheese,

Fig. 3b) or modest increases in DCq (P ≤ 0�05, reduced-and low-fat cheeses, Fig. 3b). Similarly, small but signifi-

cant changes in DCq (P ≤ 0�05) were also observed with

bifidobacteria-added cheese (Fig. 3c), showing that bifi-

dobacteria also survived, with some loss of viability on

one strain, which matches assessment by standard qPCR

that showed some loss of bifidobacterial viability in 270-

day-old Cheddar cheeses (Table 4 and Fig. S3). Addi-

tional bifidobacterial species need to be assessed for their

viability in cheese. However, application of the PMA

assay confirmed that qPCR detected viable LAB and bifi-

dobacteria in the cheese matrix and that starter lactococ-

ci, NSLAB and probiotic lactobacilli, and bifidobacteria

remained viable throughout 270 days of Cheddar cheese

ageing.

Discussion

To consistently produce commercial cheeses, the manu-

facturing process of aged semi-hard and hard cheeses is

designed to physico-chemically control their microbial

diversity. For example, Cheddar cheese is initially inocu-

lated with high numbers of starter lactococci (105–106 CFU ml�1 milk) that replicate rapidly during cheese

(a)

(b) (c)

14

12

10

8

6

4

2

00

9876543210

0 180

50 100 150 200 250 300

Time (days)

Time (days)

ΔCq

(with

- w

ithou

t PM

A)

ΔCq

(with

- w

ithou

t PM

A) 18

1614121086420

0 180Time (days)

ΔCq

(with

- w

ithou

t PM

A)

Figure 3 Comparisons of live lactococcal (a),

probiotic Lactobacillus acidophilus (b), and

probiotic Bifidobacterium lactis (c) populations

by determining qPCR Cq times from cheese

samples’ DNA extracted with and without

propidium monoazide addition. Data are

presented as the difference in Cq times, DCq,

as explained in Materials and Methods.

Vertical error bars represent standard

deviations of DCq assessed from two

replicates. In panel a, □ full-fat control

(probiotic bacteria not added during

cheesemaking), ■, low-fat control (probiotic

bacteria not added during cheesemaking), 4,

Bif. lactis Bif-6 added to full-fat cheese, ♢

Bif. lactis Bif-6 added to low-fat cheese, ○,Lactobacillus casei L10 added to full-fat

cheese, ●, Lact. casei L10 added to low-fat

cheese. In panel b, white bars, full-fat cheese,

grey bars, reduced-fat cheese, and black bars,

low-fat cheese, all containing

Lact. acidophilus LA-5 added to cheese. In

panel c, white bars, full-fat cheese, grey bars,

reduced-fat cheese, and black bars, low-fat

cheese, all containing Bif. lactis Bif-6 added

to cheese. Statistical significance over time

was determined only within each cheese.



manufacture and chiefly degrade lactose to produce lactic

acid and reduce cheese pH during early ageing. When

adjunct or probiotic bacteria are included, the balance of

LAB populations may be altered.

Chiefly, the added probiotics must survive in sufficient

numbers (target 3�6 9 106 to 3�6 9 107 CFU g�1 cheese,

to deliver 109 bacteria per serving) throughout long-term

ageing of cheese to provide desired health benefits upon

human consumption (Medici et al. 2004; Ouwehand

et al. 2012). Among the added lactobacilli, Lact. casei and

Lact. paracasei are commonly found in Cheddar cheese,

are even used as adjuncts and are expected to survive

throughout cheese ageing (Peterson and Marshall 1990).

To detect added probiotic bacteria, we applied primers

previously designed in other studies (Table 3) after select-

ing for specificity against the strains used in our study.

Better sensitivity was achieved compared to previous

studies by improving DNA extraction from Cheddar

cheese using phenol–chloroform-based methods (min.

100 CFU g�1 detected; Fig. S1). By applying genus- and

species-specific primers, we were able to distinctly enu-

merate probiotic lactobacilli and NSLAB lactobacilli. The

consistent presence of NSLAB lactobacilli at 10- to 100-

fold higher levels precluded any interference by added

probiotic lactobacilli in NSLAB enumeration. The use of

qPCR also provided a specific and reliable quantitative

assay throughout cheese ageing, as opposed to growth

media-based enumeration techniques (McSweeney et al.

1993; Gardiner et al. 1998; Crow et al. 2001; Oberg et al.

2011) where the distinction between starter and NSLAB

becomes difficult beyond 90 days of age. At certain cheese

ages, bacterial levels estimated by qPCR varied by as

much as 10- to 1000-fold, which appears to be common

in the cheese matrix based on other studies that used

media-based enumeration approaches (Table 1).

Total lactobacilli were present at much higher levels of

108 to 109 CFU g�1 initially than expected (<100 CFU

g�1) postmanufacture. This indicates insufficient sanita-

tion, which led to high levels of NSLAB in the 136-kg

milk cheese vats. In higher scale manufacture (>500 kg

milk per batch), equipment is frequently subject to clean-

ing-in-place, which provides excellent control over

unwanted NSLAB presence. However, even at this high

initial NSLAB level, we could still distinguish added pro-

biotic from NSLAB, which demonstrated the strength of

using qPCR to detect added bacterial species.

Added probiotic lactobacilli survived in cheese over

270 days of ageing, even growing 10 to 1000-fold

(Table 4, Fig. S2). This observation is not surprising,

considering that NSLAB lactobacilli are acquired from

different sources and only found at low levels (<100 CFU

g�1) in early stages of cheesemaking, but attain levels of

105–107 CFU g�1 over 3–6 months of ageing (Beresford

et al. 2001). Other studies that compared survival of dif-

ferent lactobacilli in cheese have confirmed the presence

of Lact. paracasei up to 300 days of cheese age (Gardiner

et al. 1998; Fitzsimons et al. 2001). Potentially, members

of the same genus likely share survival and metabolic

characteristics that allow them to adapt to the cheese

environment. Comparative genomics studies have verified

that members of the genus Lactobacillus share 383 orthol-

ogous genes across 20 distinct genomes (Makarova et al.

2006), which is likely a common core gene set that allows

survival of lactobacilli in a dairy matrix. However, sur-

vival of probiotic lactobacilli differed across cheese types.

The pattern of Lact. acidophilus strains’ survival was

not influenced by cheese fat levels, whereas Lact. casei

and Lact. paracasei strains survived differently due to fat,

although all three species increased in numbers over

cheese age. The rationale for variable survival of species is

not evident, because other studies have shown that

Lact. casei survives equally well in all these cheese types

(Fenelon et al. 2000; Midje et al. 2000). Both Lact. casei

and Lact. paracasei are common species of NSLAB in

Cheddar cheese and likely are better adapted to cheese

environments. Many previous studies have used Lact. ca-

sei and Lact. paracasei strains as adjuncts for reduced-fat

cheeses (Midje et al. 2000; Swearingen et al. 2001; Dasen

et al. 2003), but none have yet reported the associated

challenges for survivability in such conditions. One likely

explanation is lower salt-in-moisture (3%) in full-fat

cheese compared to reduced- or low-fat cheeses (4%)

that may allow starter bacteria to metabolize lactose fas-

ter, leading to sugar starvation and further, an earlier

shift into the nonculturable state (Ganesan et al. 2007).

The nondividing lactococci may hence be a lesser chal-

lenge to the added lactobacilli, whereas the later the lac-

tose reduction, starter nonculturability is delayed and so

is growth of lactobacilli. However, this explanation only

fits the increase in levels of strains CRL-431 and F19, and

not L26, which survived better in full-fat cheese. Addi-

tional genes in the genomes of lactobacilli outside the

common core set (Makarova et al. 2006) may be involved

in the ability of probiotic lactobacilli to survive differently

in cheese.

Bifidobacteria are common inhabitants of animal and

bird gastrointestinal systems (Gomez-Donate et al. 2012).

Their survival in cheese has been previously demonstrated

(Mc Brearty et al. 2001) but needs further comprehen-

sion, as cheese contains lactose as the abundant sugar

that is utilized by the starter bacteria and NSLAB (Crow

et al. 1993), thus limiting available sugar for bifidobacte-

ria. The species, Bif. lactis, used in this study is putatively

a dairy-adapted derivative of Bif. animalis (Garrigues

et al. 2010) and may survive effectively in cheese. How-

ever, the two Bif. lactis strains added to cheese showed



differing survival patterns in cheeses, with one surviving

poorly in full-fat cheese and the other exhibiting low sur-

vival in low-fat cheese. The variable survival of bifidobac-

terial species in even one cheese type has been reported

previously (Mc Brearty et al. 2001). Our observation and

that of Mc Brearty et al. (2001) suggests that alteration of

fat level effectively changes physico-chemical conditions

inside the cheese matrices and thus alters the survival of

members of the same genus.

We also verified that the addition of different probiotic

lactobacilli influenced the levels of total lactobacilli in

Cheddar cheese, as for example, inclusion of Lact. aci-

dophilus La-5 and Lact. casei CRl431. This is interesting,

considering that probiotics were added at 10- to 1000-

fold lower levels than total lactobacilli, and highlights that

even minor components of the cheese flora are likely to

alter the major component flora, though not universally.

This is likely due to the initial inoculum of an adjunct at

a higher level than its adventitious entry into the cheese

matrix that consequently favours its later competitive

existence. Total lactobacilli levels also changed in other

cheeses influenced by cheese type. This observation has

been partially confirmed by other groups using microbial

plating for enumeration (Gardiner et al. 1998; Swearingen

et al. 2001; Dasen et al. 2003) that were, however, limited

in distinguishing added adjuncts from other NSLAB.

In relation to LAB viability in cheese, the ‘lactococcal

lysis’ theory proposes that starter lactococcal species usu-

ally die during Cheddar cheese ageing as evidenced by

microbial selective enumeration (Fenelon et al. 2000).

Supposedly, the lysed cells release intracellular enzymes

into the cheese matrix that further degrade the caseins

into peptides and amino acids for NSLAB metabolism

(Crow et al. 1995; Buist et al. 1997, 1998). In a complex

ecology such as cheese, with multiple species present,

assessing the release of intracellular enzymes into the

cheese serum phase is nonspecific (O’Sullivan et al. 2000)

and thus not reliable. However, bacterial lysis may release

DNA into cheese that remains stable and contributes to

live bacterial estimates during qPCR. The absence of such

extracellular DNA was established by attempting qPCR

detection from DNase-treated cheeses using species-spe-

cific primers (Fig. 2). Hence, extracellular DNA did not

contribute towards qPCR amplification. Further, using

the selectively permeating PMA that binds intracellular

nucleic acids in dead or membrane-compromised cells,

we found that lactococci, other NSLAB and probiotic lac-

tobacilli all remained viable in Cheddar cheese over

270 days of ageing (Fig. 3). The reduced viability of bifi-

dobacteria was expected based on qPCR assays and was

further confirmed by PMA assays. These findings cumula-

tively demonstrated that qPCR, even without PMA addi-

tion, only estimates viable cell populations in cheese and

not that of dead cells. More importantly, these findings

highlight the ability of lactococci to survive in Cheddar

cheese throughout ageing, which was expected based on

prior studies that demonstrated lactococcal nonculturabil-

ity in culture (Ganesan et al. 2006, 2007). Potentially,

with casein-derived amino acids being abundant in

cheese, lactococci may survive in the nonculturable state

in cheese and acquire metabolic energy via previously

proposed mechanisms, such as Arg (Chou 2001; Chou

et al. 2001) and branched chain amino acid degradation

(Ganesan et al. 2006). While probiotic lactobacilli share

similar genetic repertoires to lactococci, their ability, or

that of the genetically distinct bifidobacteria, to use such

mechanisms for survival remains to be established.

In conclusion, different strains of probiotic lactobacilli

and bifidobacteria were added to full-, reduced- and low-

fat Cheddar cheeses to understand their survivability

under these diverse physico-chemical environments. We

demonstrated that both the starter LAB and probiotic

bacteria survived throughout ageing, indicating the suit-

ability of semi-hard, aged cheeses as suitable vehicles for

probiotic delivery. Probiotic lactobacilli survived differ-

ently at the species level. Some added probiotics also

altered the levels of total lactobacilli and starter bacteria,

even when present at levels 10- to 1000-fold lower. Fur-

ther, we also demonstrated that starter, NSLAB and pro-

biotic bacteria remained viable with an intact cell

membrane throughout the period of cheese ageing.

Acknowledgements

The authors acknowledge the assistance of and thank

Brian Pettee for cheesemaking and sampling and Reed

Gann for qPCR primer design.

Conflict of Interest

No conflict of interest declared.

Funding source

The study was accomplished by a grant to CB and DJM

that was funded by Dairy Management Inc. and adminis-

tered by the Dairy Research Institute (Rosemont, IL).

Authors’ contributions

CB, DJM and BW conceived the project; CB and DJM

made cheese with added probiotic bacteria; BW guided

JP, ND and GR, who performed DNA extraction and

qPCR; BG and BW conducted data analyses and authored

the manuscript.



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Supporting Information

Additional Supporting Information may be found in the

online version of this article:

Data S1 Materials and methods.

Table S1 Proximate composition (averages) of Ched-

dar cheese made at different fat levels.

Table S2 Limit of detection for different probiotic bac-

teria using species primers in Cheddar cheese.

Table S3 Analysis of main effects across all probiotics

added.

Table S4 Differences in probiotic survival by genus.

Table S5 Impact of probiotic Lactobacillus strains on

NSLAB levels in cheese.

Figure S1 Standard curves of bacterial counts for qCR-

based estimation.

Figure S2 Different methods for DNA extraction yield

different results for lactococcal detection by qPCR.

Figure S3 Levels of added probiotic Lactobacillus in

Cheddar cheeses over 9 months of ageing, estimated by

qPCR.

Figure S4 Levels of added probiotic Bifidobacterium

lactis in Cheddar cheeses over 9 months of ageing, esti-

mated by qPCR.

Figure S5 Levels of total lactobacilli in probiotic Lacto-

bacillus-added Cheddar cheeses over 9 months of ageing,

estimated by qPCR.



probiotic bacteria survive in cheddar cheese and modify populations of other lactic acid bacteria

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