Microbiological stability and thermal inactivation of skim milk ... · Due to its presence in both...

U N I V E R S I T Y O F C O P E N H A G E N FACULTY OF SCIENCE

Microbiological stability and thermal inactivation of skim milk concentrates produced by RO filtration

MSc thesis – Dairy Science and Technology

Philip Zingenberg, (xlv766)

Main Supervisor: Lilia Arhné

Date of Submission: 7th of August 2017

III

Abstract Concentrates of milk or whey are already in use as intermediate products in the production of protein

powders, as well as in the production of some cheeses. Typically, concentrations have been obtained through

the use of evaporators but application of non-thermal membrane technology is emerging taking benefits of

the differences in physical and chemical properties of the different components and offering large

advantages in terms of product quality and energy consumption. This innovative approach has a large

potential in terms of improving sustainability of dairy production, creating new opportunities for export, and

boosting a new generation of dairy products. Understanding the microbiological stability during RO

concentration and heat treatment of dairy concentrates is of major importance to guarantee safety and

product quality. The type of microorganisms in RO retentates is expected to differ widely depending on the

quality of the milk used and the production practices. Furthermore, their growth and thermal resistance are

influenced by factors such as dry matter contents, moisture contents (aw) and pH/salt balance of the

concentrates.

The overall purpose of this study has been to identify, select and study the growth and thermal inactivation

of representative microorganisms normally found in RO concentrates. Concentrates from pasteurized and

raw milk from two dairies and from the RO pilot plant unit at UCPH were used in this study. The identification

was done using Next Generation Illumina Sequencing and 16S rRNA gene sequencing. The study showed that

the microbial composition in the thermized UF concentrate from a dairy plant was dominated by especially,

Thermus spp. and Pseudomonas spp.. Furthermore, the microbial composition of the concentrates also

varied markedly between production days as expected. The microflora of the RO concentrate made from

raw skim milk in the pilot plant at UCPH revealed a combination of Gram-positive and Gram-negative

bacteria, which were commonly associated with the psychrotrophic microflora of raw bulk milk. The

microflora of RO concentrate made from pasteurized skim milk was particularly dominated by

Microbacterium lacticum.

Due to its presence in both the UF and the RO concentrate, its thermoduric ability to survive pasteurization

processes and its proteolytic and lipolytic activity, M. lacticum was selected for the thermal inactivation

study. M. lacticum were isolated and inoculated in RO concentrates with different dry matter contents (15%,

20%, 25% and 30% DM). These concentrates were subsequently heat treated at temperatures between 57-

72oC up to 180s. The magnitude of microbial inactivation caused by the thermal treatment was markedly

influenced by the dry matter content in the RO retentates. The slowest rate of inactivation was observed for

concentrates with 30% DM. At 72oC, M. lacticum seemed to be completely inactivated in all samples already

after 30s.

IV

Preface

This MSc thesis comprises the results obtained by Philip Zingenberg from February to August 2017. The

experimental work was carried out at Department of Food Microbiology and Department of Ingredient and

Dairy Technology at University of Copenhagen, Denmark and at Arinco Dairy - Arla Foods. The project was a

collaboration between Arla Foods, GEA and University of Copenhagen.

Main Supervisor

Lilia Arhné, Professor, Department of Ingredient and Dairy Technology, University of Copenhagen.

Co-supervisors

Finn K. Vogensen, Associate Professor, Department of Food Microbiology, University of Copenhagen,

Anni B. Hougaard, Adjunct, Department of Ingredient and Dairy Technology, University of Copenhagen,

Nils Mørk, Junior Technology Engineer, GEA Filtration, Skanderborg, Denmark,

Tommas Neve, Senior Process Engineer, Arla Foods, Aarhus, Denmark.

Philip Zingenberg (xlv766)

V

Acknowledgements

I would like to give my sincere thanks to my main supervisor Lilia Arhné for her very useful guidance,

assistance and patience throughout the entire project.

Furthermore, sincere thanks are also given to my co-supervisors, Finn K. Vogensen, Anni B. Hougaard, Nils

Mørk and Tommas Neve for providing me with valuable guidance, knowledge and support. Moreover, Nils

Mørk deserves special thanks for his assistance during the RO production trials at UCPH.

I would like to give a special thanks to laboratory technician, Basheer Aideh for his invaluable assistance and

help in the laboratory.

I would also like to thank Lukasz Krych and Josue Meji for their assistance and help in the Illumina sequencing

analysis’. Finally, my thanks to the staff at Arinco dairy for their assistance when collecting and analyzing the

RO concentrate samples and to the Slagelse dairy for providing the raw skim milk for the RO production trials

at UCPH.

VI

Table of Contents Abstract ................................................................................................................................................ III

Preface ................................................................................................................................................. IV

Acknowledgements ................................................................................................................................ V

List of abbreviations ............................................................................................................................ VIII

1. Project overview ............................................................................................................................. 9

1.1. Introduction ....................................................................................................................................... 9

1.2. Aim of study ..................................................................................................................................... 10

1.3. Objectives ........................................................................................................................................ 10

1.4. Experimental design ........................................................................................................................ 11

2. Background .................................................................................................................................. 13

2.1. Microflora of raw milk and pasteurized milk .................................................................................. 13

2.1.1. Raw milk .................................................................................................................................. 13

2.1.2. Pasteurized milk ...................................................................................................................... 15

2.2. Identification and Next Generation Sequencing ............................................................................. 16

2.3. Overview of membrane technologies ............................................................................................. 20

2.4. Thermal inactivation of microorganisms ......................................................................................... 24

2.4.1. Unsteady-state heat transfer and thermal inactivation experiments ..................................... 26

2.5. Literature review on microbiological and milk aspects during membrane filtration ...................... 27

3. Materials and methods ................................................................................................................. 30

3.1. UF samples from Slagelse dairy ....................................................................................................... 30

3.1.1. Cell harvest for DNA preparation ............................................................................................ 30

3.2. RO samples from Arinco dairy and production trials at UCPH ........................................................ 31

3.2.1. Cell harvest for DNA preparation ............................................................................................ 31

3.3. InstaGene DNA extraction for Rep-PCR and 16s rRNA sequencing................................................. 31

3.4. Repetitive Sequenced-Based PCR (rep-PCR) ................................................................................... 31

3.5. Amplification and sequencing of the 16S rRNA gene ...................................................................... 33

3.6. Gram-test and catalase-test ............................................................................................................ 34

3.7. Illumina sample preparation procedure .......................................................................................... 35

3.7.1. Extraction of DNA for Illumina sequencing ............................................................................. 35

3.7.2. Assembling the 1st PCR (amplification of the V3 region of 16s rRNA): .................................... 36

3.7.3. 2nd PCR (barcoding of the amplified samples for sequencing) ................................................ 38

3.7.4. Cleaning of library (PCR amplicons) ......................................................................................... 40

VII

3.7.5. Measuring the concentration of the purified library .............................................................. 41

3.8. Production of RO milk concentrate/retentate ................................................................................ 42

3.8.1. Operating procedures and preparations of the RO pilot unit ................................................. 43

3.8.2. Production ............................................................................................................................... 44

3.9. Determination of total solids content ............................................................................................. 45

3.10. Thermal inactivation of M. lacticum in RO skim milk concentrate ............................................. 45

3.10.1. Preparation .............................................................................................................................. 45

3.10.2. Experiment .............................................................................................................................. 46

4. Results and discussion .................................................................................................................. 48

4.1. Ultra-filtrated concentrate .............................................................................................................. 48

4.1.1. Illumina results based on DNA from 38 UF-sample collected at Slagelse dairy ...................... 48

4.2. Reverse-osmosis concentrates ........................................................................................................ 57

4.2.1. Total CFU/ml measured at the start and at the end of the RO productions ........................... 57

4.2.2. Illumina results ........................................................................................................................ 60

4.2.3. Rep-PCR and Cluster analysis .................................................................................................. 60

4.2.4. 16S rRNA gene sequencing results .......................................................................................... 63

4.3. RO concentrate manufacture process chart ................................................................................... 69

4.4. Heat-inactivation of M. lacticum in raw RO skim milk retentates .................................................. 71

4.4.1. Estimated heat-up and cool-down times tubes during the thermal inactivation experiments ..

................................................................................................................................................. 72

4.4.2. Thermal inactivation experiments ........................................................................................... 74

5. Project conclusion ........................................................................................................................ 81

6. Future perspectives ...................................................................................................................... 82

7. Literature ..................................................................................................................................... 83

Appendix ............................................................................................................................................. 88

VIII

List of abbreviations

MF Microfiltration

NF Nanofiltration

UF Ultrafiltration

RO Reverse osmosis

CFU Colony forming unit

PCA Plate count agar

ON Over-night

DM Dry matter

UCPH University of Copenhagen

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1. Project overview

1.1. Introduction

Milk is a complex solution of different constituents such as water, protein, fat, lactose and minerals. These

components possess specific nutritional and functional properties. Therefore, fractionation or concentration

of these components in order to obtain pure ingredients or to reduce volume has been an essential part of

the dairy industry for several years. It is estimated that approx. 500,000 m2 of membrane area is installed

throughout the global dairy industry worldwide. Furthermore, it is estimated that approx. 70% of this area is

used for the processing of whey products (Marella et al., 2013).

Concentrates of milk or whey are already used as intermediate products in the production of protein

powders, as well as in the production of some cheeses. Typically, the concentration has been done by

evaporators but application of non-thermal membrane technology is emerging taking benefits of the

differences in physical and chemical properties of the different components offering large advantages

(Marella et al., 2013). Examples of such advantages could be lower heat-load applied to the milk during milk

powder production and reduced energy consumption (Henning et al., 2006). This innovative approach holds

large potentials in order to improve sustainability of dairy production, create new opportunities for export,

and boost a new generation of dairy products (e.g. low-heat milk powders with improved functional

qualities). Furthermore, pre-concentration of raw milk at the farm using membrane filtration allows for

decreasing the volume of milk and reducing the transportation costs without altering the sensory quality of

the milk (Kumar et al., 2013).

Until now, these concentrates, as intermediate products, are often not stored for a long time before further

processing. However, there is a growing interest in stable milk concentrates as ingredients for manufacturing

dairy products. Hence, this innovative approach will also generate new challenges in post-processing such as

storage stability of the concentrates due to storage or transportation for extended periods of time.

Furthermore, understanding the microbiological stability during RO concentration and heat treatment of

dairy concentrates is of major importance to guarantee safety and product quality. The type of

microorganisms in RO retentates is expected to differ widely depending on the quality of the milk used and

production practices (Ledenbach & Marshall, 2009). Furthermore, their growth and thermal resistance will

be influenced by factors such as dry matter contents, moisture contents (aw) and pH/salt balance of the

concentrates (Kumar et al., 2013).

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1.2. Aim of study

Knowledge about microbiological stability and thermal inactivation of concentrates is needed to produce

safe and high quality dairy products. Currently, no published studies have investigated the microbiological

composition of reverse osmosis skim milk concentrates. One study has investigated the bacteria responsible

for biofilm formation in RO membranes systems. Studies, however, which have isolated and identified

microorganisms within the RO of skim milk retentates have not been found. Furthermore, only few studies

have investigated the thermal inactivation of microorganisms in RO skim milk and the effect of dry matter on

microbial inactivation. Therefore, the aim of this project has been to identify, select and study the growth

and thermal inactivation of representative microorganisms normally found in RO skim milk concentrates.

1.3. Objectives

In order to fulfill the aim of this study, the specific objectives of this work were:

- To evaluate the microbiological composition of milk concentrates through the application of Next

Generation Illumina Sequencing,

- To isolate and identify microorganisms from RO concentrates made from both raw and pasteurized

skim milk using a combination of standard agar plating and molecular methods such as DNA

fingerprinting (rep-PCR), 16S rRNA gene sequencing accompanied by phenotypic tests (Gram- and

catalase-tests), and lastly

- To study the thermal inactivation of a selection of microorganisms in raw non-concentrated milk,

15% DM, 20% DM, 25% DM and 30% DM using four different temperatures (57oC, 62oC, 67oC and

72oC). The data were used to calculate their D-values and z-values in order to identify the required

thermal processing conditions.

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1.4. Experimental design

Figure 1, shows an overview of the experimental work which was carried out during this project. The overall

approach of this study has been inspired by the polyphasic approach which is currently the most popular

method for classification of bacteria and other microorganisms. The principle of the polyphasic approach is

to combine genotypic, chemotaxonomic and phenotypic methods in order to determine the taxonomic

position of the microorganism (Prakash et al., 2007).

In the first part of the study, only heat-treated UF concentrate from Slagelse dairy was available for this

project. Fortunately, however, it became possible to go to Arinco dairy in Videbæk, Jutland to collect and

analyze the RO concentrates on site. Furthermore, GEA had provided an RO filtration unit making it possible

to produce RO retentates from raw skim milk at UCPH. This allowed us to simulate an industrial application

where raw milk would be filtrated directly without prior heat treatment.

With all these different skim milk concentrates, it seemed possible to form a wide spectrum of the microbial

community in UF and RO skim milk concentrates.

Samples of concentrates were plated on 1% milk PCA in order to evaluate the growth of microorganisms

growing within the concentrates. DNA was extracted from both the microorganisms growing on the agar

plates and directly from the concentrates. This was done in order to perform the molecular identification

analyses (rep-PCR, 16S rRNA gene sequencing and Illumina sequencing).

In the second part of the study, specific microorganisms isolated from the RO skim milk retentates were

selected for thermal inactivation experiments. These trials were conducted in RO retentates produced at

UCPH with varying dry matter contents and at different temperatures. Eventually, D- and z-values were

calculated.

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Figure 1. Shows an overview of the experimental design of this project. The project consisted of two parts. Part I: Collecting of samples of UF concentrates from Slagelse dairy, RO concentrates from Arinco dairy and UCPH, conducting laboratory analyses, including rep-PCR, 16S rRNA gene sequencing and Illumina sequencing. Part II included the selecting of microorganisms for the thermal inactivation experiments, the thermal inactivation experiments and eventually determination of D- and z-values.

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2. Background

2.1. Microflora of raw milk and pasteurized milk

2.1.1. Raw milk

Milk is a highly nutritious food product, which contains abundant water, nutrients and pH which is nearly

neutral (Ledenbach & Marshall, 2009). This creates an ideal medium for growth and development of a wide

range of microorganisms found in the food environments. Even though, raw milk from non-infected bovine

udders can contain low levels of somatic cells and non-pathogenic microorganisms, freshly lactated milk can

be considered as nearly sterile (Hutchison et al., 2005). However, with the increased number of milkings, the

number of bacteria isolated from milk drawn aseptically from the cow’s teats also tends to increase

(Ledenbach & Marshall, 2009). This is often caused by an increased stress applied to the teats and mammary

glands as a consequence of increased milk production as well as the action of the automatic milking machine

(Ledenbach & Marshall, 2009). Consequently, the tight junctions in the teats become more loose and open

whereby microorganisms can enter the canal and eventually cause mastitis (Ledenbach & Marshall, 2009).

Most often, mastitis is caused by Stapholycoccus spp., Streptococcus spp. or Gram-negative pathogens

(Oliveira et al., 2012) The somatic cell count (SCC) is a suitable predictor of subclinical mastitis, since the SSC

increases during the inflammatory processes due to increasing numbers of infectious bacteria (Barbosa et

al., 2013). The increased number of SCC also affects the physio-chemical characteristics, composition and

yield of milk negatively (Barbosa et al., 2013).

However, most of the microorganisms that are found in the raw milk are environmental contaminates. These

are ubiquitous in the environment and most enters the milk due to contamination from the surface of the

udder and teats, the milking equipment, or from the storage tanks (Hayes et al., 2001; Hutchison et al., 2005).

Consequently, the raw milk naturally has a very diverse microbial community, which indeed is known to

influence organoleptic characteristics of raw milk cheese (Lafarge et al., 2004). Even though, psychrotrophic

bacteria account for <10% of the initial microbial flora in raw milk, these tend to dominate the microbial

community during cold storage (Rasolofo et al., 2010). However, the problem arises during prolonged

storage of the milk allowing these bacteria to grow and form extracellular thermostable enzymes. These are

not inactivated during pasteurization and will affect the quality of the final dairy product (Franciosi et al.,

2011; Rasolofo et al., 2010). Furthermore, spore-forming bacteria are able to produce spores and these can

be activated and start germinating during heat treatment of the milk (Rasolofo et al., 2010).

Within the global dairy industry, bonus payment systems have been developed by the dairy companies

creating incentives for the dairy farmers to optimize on-farm hygiene in order to produce milk with low

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CFU/ml. The bonus systems are based on the total viable counts or total bacterial counts (TVC or TBC) as an

universal indicator for the microbial quality of the raw milk (Hayes et al., 2001; Hutchison, et al., 2005). The

bonus system was introduced in the mid-1980’s in the United Kingdom and subsequently adopted by the

European Commission (Hutchison et al., 2005). According to the Danish Dairy Board (2008), the Danish

farmers are paid 1% extra if the count of vegetative cells is <30,000 CFU/ml, no extra if the count is between

31,000 – 50,000 CFU/ml and if the count is between 51,000 – 200,000 or above 200,000, the farmers are

charged 4% or 10% respectively (Danish Dairy Board, 2008).

According to Lafarge et al. (2004) only few studies have been carried out in order to characterize the microbial

flora of raw milks. Currently, the identification has only been focusing on enumeration of the most

represented groups of microbiological flora and with only partial identification (Lafarge et al., 2004).

In general, the most predominant microflora in raw milk includes species of lactic acid bacteria (LAB)

Lactococcus and Lactobacillus spp., Pseudomonas spp., Micrococcaceae (Micrococcus and Staphylococcus

spp.) and yeast. Other LAB such as Leuconostoc, Enterococcus, and Streptococcus spp. along with Bacillus,

Clostridium and Listeria spp. and Enterobacteriaceae (Holm et al., 2004; Lafarge et al., 2004; Lindberg et al.,

1998; Masoud et al., 2012). Gram-negative bacteria such as Acinetobacter, Alcaligenes, Flavbacterium and

Aeromonas as well as Gram-positive Arthrobacter, Corynebacterium, Brevibacterium and Propionibacterium

species can also be found in raw milk (Lafarge et al., 2004).

Lafarge et al. (2004) also claimed that the cleaning procedures and hygienic practices of the farmers very

much influence the diversity of spoilage microorganism in the milk. For instance, intensive washing of the

milking equipment and individual cleaning of the teats resulted in the majority of the spoilage microorganism

listed above ended up in the milk (e.g. coliforms and Pseudomonas spp.) (Lafarge et al., 2004). On the other

hand, if the udder was subject to minimal cleaning, this would preserve the microorganism such as the more

salt-tolerant bacteria; Micrococcus, Arthrobacter, Microbacterium, Brevibacterium and Stapholycoccus

aureus including the LAB.

Holm et al., (2004) stated that contaminating bacteria from the teats have been reported such as Micrococcus

spp., coagulase-negative Staphylococcus spp., Enterococcus spp., coryneforms, Bacillus spp., coliforms as well

as other gram-negative rods. Furthermore, milk deposits and residual washing water on insufficiently cleaned

milking equipment or bulk tanks would promote growth of microorganisms, however, favor the fast growing

bacteria such as Lactococcus spp. (Holm et al., 2004).

Additionally, factors such as health status of the cattle, type of feed; forage or ensilage and seasonal variation

may also influence the microbial flora of the raw milk (Franciosi et al., 2011; Lafarge et al., 2004).

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2.1.2. Pasteurized milk

Pasteurization of the raw milk at either high temperature short time (HTST: 72oC for 15s) or low temperature

long time (LTLT: 63oC for 30s) should, however, eliminate all viable vegetative pathogenic microorganisms

and decrease the microbial load in the raw milk (Murphy et al., 1999; Oliveira et al., 2015). However, the

efficiency of the pasteurization and eventually the quality of the final dairy product are strongly depending

on the microbiological quality of the raw milk (Oliveira et al., 2015).

Unfortunately, the psychrotrophic, mesophilic and thermophilic spore-forming Bacillus spp. (e.g. B. cereus

and B. linchenformis) are not eliminated during pasteurization (Murphy et al., 1999). Furthermore, growth of

the obligate or facultative thermophiles may be an issue during manufacturing of milk powder since they can

proliferate at ranges of 40-75oC and 35-70oC, respectively (Murphy et al., 1999). These temperature

conditions are fulfilled during the evaporation of water during the concentration of the milk whereby they

may colonize in the heating equipment (Murphy et al., 1999). This in combination with operation times of

nearly 20 hours, will lead to serious risks of plant contamination and unacceptable high numbers of spores

ending up in the finally dried milk powder (Murphy et al., 1999). Contamination of thermophiles might as

well arise from reuse of by-products such as buttermilk, permeate from milk ultrafiltration or from addition

of ingredients such as lactose. Furthermore, both spores and vegetative cells are able to attach to the surface

of stainless steel and fouled surfaces (Scott et al., 2007) . Therefore, contamination of the milk is also likely

to be a result of biofilm formation, which can be of one single species but more often consists of a diverse

community of different microorganisms (Oliveira et al., 2015). Thermophiles are typically eliminated during

cleaning (CIP). Foulants or biofilms, however, are able to protect spores as well as vegetative cells from the

chemicals applied during CIP (Scott et al., 2007). This allows the bacteria to remain inside the processing

equipment and cause recontamination during the following production run (Scott et al., 2007).

Additionally, post-pasteurization contamination of the milk is a well-known phenomenon and numbers of

studies have been carried out dealing with contamination of milk and dairy products. According to Ledenbach

& Marshall (2009) especially psychrotrophs and spore-forming bacteria are responsible for the post-

pasteurized contamination of milk and these tend to originate from water or air in the filling equipment or

the immediate surroundings where these have been able to proliferate over a prolonged period of time

(Oliveira et al., 2015).

However, the risk of contamination during post-pasteurization has been significantly reduced due to the fact

that most dairies are operating with enclosed pipeline systems and improved cleaning procedures (CIP)

limiting biofilm formation as well as using better sanitary design of equipment (Barbano et al., 2006;

Ledenbach & Marshall, 2009).

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2.2. Identification and Next Generation Sequencing

Traditionally, the characterization of the microbial community was carried out using classical culture-

dependent methods which tend to be both time-consuming and tedious (Lafarge et al., 2004; Rasolofo et al.,

2010). Furthermore, these methods often provide only partial information about the composition of the

microbial community and microbial enrichment is necessary to allow a more accurate characterization of the

microbial dynamics in complex ecosystems (Lafarge et al., 2004). Additionally, the selective isolation of

microorganisms sometimes requires unknown growth conditions present only in the natural habitats which

are not reproduced in laboratory media (Mayo et al., 2014; Rasolofo et al., 2010). Consequently, some

microorganism present in low numbers might be outcompeted by other species being numerically abundant

and thereby subject to undetection in the culture (Mayo et al., 2014).

For several years, 16S rRNA gene sequences have been used to study the phylogeny and taxonomy of

unidentified bacteria (Janda & Abbott, 2007). The 16S rRNA gene is the most common housekeeping genetic

marker, due to the fact that it is present in almost all bacteria, is well conserved and has not changed over

time. Lastly, the gene is large enough for informatics purposes (approx. 1500 base-pairs) (Janda & Abbott,

2007). The 16S rRNA gene sequences often allow for identification of the unknown bacteria on genus and

species level even though it can be difficult sometimes to distinguish between species that are closely related.

Prokaryotes with ≥ 97% similarity to the database reference sequence can be considered the same species. ,

Similarities < 97%, however, can be considered members of a different species (Mayo et al., 2014).

During recent years, several studies have been carried out dealing with monitoring changes in microbial

communities in both raw milk and dairy products based on culture independent methods such as denaturing

gradient gel electrophoresis (DGGE), temporal temperature gradient electrophoresis (TTGE) and single strand

conformation polymorphism (SCCP) (Lafarge et al., 2004; Rasolofo et al., 2010). Furthermore, an approach

where both the culture-dependent method and the direct recovery of 16S rRNA gene sequences have been

used to characterize the microbial composition of milk has been described (Rasolofo et al., 2010).

In addition, so-called next generation sequencing (NGS) have been developed (Mayo et al., 2014). These

revolutionizing techniques are high-throughputs techniques which means that they can produce millions of

sequences at the same time. Furthermore, these sequences form a basis for accurate identification of

microbial taxa including microorganisms present in low numbers or the unculturable ones (Mayo et al., 2014).

One of the NGS platforms called the Illumina platform was first released by a company called Solexia which

was later acquired by the company Illumina (Mayo et al., 2014). Illumina sequencing has been used to

investigate the microbial composition of facility-specific house flora in Artisan cheese-making plants located

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in the United States and to characterize the biodiversity of a complex cheese starter culture (Bokulich & Mills,

2013; Erkus et al., 2013).

The basic principles of Illumina sequencing are divided into four stages (see Figure 2);

A. Sample library preparation

There are several ways to prepares samples. A common target for the methods, however, is to add adapters

to the ends of the DNA fragments. These adapters consist of a sequencing binding site, a unique index code

(barcode) and regions which are complementary to the oligoes located on the flow cell.

B. Cluster generation

The cluster generation takes place on the surface of a flow cell. This flow cell is a glass slide with eight lanes,

each coated with a number of two types of oligoes (Shokralla, Spall, Gibson, & Hajibabaei, 2012). Cluster

generation is enabled as DNA fragments are covalently bound to the first type of oligoes which is

complementary to the adaptor region on the DNA fragment strand - the first of the two types of oligoes

(Shokralla et al., 2012). Secondly, a copy of DNA fragment-to-oligo hybridization is carried out by an

isothermal polymerase (Shokralla et al., 2012). During heating and cooling, the double stranded molecules

are denatured and the original template is washed away. The strands are clonally amplified through bridge-

amplification due to the strand bending over and hybridizing the second type of oligoes whereby the

polymerase can form a complementary strand. Eventually, two single strand copies are formed which are

attached to the flow cell once the new molecule is denatured. This process is repeated several times and

occur simultaneously for millions of clusters, which eventually generates clonal amplification of all the

fragment in the library.

After the bridge-amplification, the reverse-strands are washed off. The free primer-ends are blocked in order

to avoid unwanted priming (Illumina, 2017).

C. Sequencing

After cluster generation, the sequencing is taking place. This step is also called sequencing-by-synthesis,

which means that a proprietary reversible terminator-based method is utilized. This method detects the

single bases once they are incorporated into the DNA template strand. Four fluorescently tagged nucleotides

incorporated with a 3´-OH-group are competing for the addition to the growing strand. However, the 3’-OH

ensures that only one nucleotide is added to the strand per each cycle (Shokralla et al., 2012). Once the

nucleotide has been added to the cluster, a excitation occurs together with a chemically de-blocking, allowing

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the next nucleotide to add to the cluster (Shokralla et al., 2012). The excitation is followed by an image step,

which identifies the incorporation of the nucleotide in the cluster (Shokralla et al., 2012). Once the first read

of the strand has been carried out, the read product is washed away and read for the first index code is

sequenced. Following this, the forward strand bends over and binds to the second oligo on the flow cell. At

this point the index two is sequenced in the same manner as for index one and the polymerase extents the

second flow cell oligo forming a bridge. This bridge is eventually linearized and the forward strand is cleaved

off and washed away. The primer end for the reverse strand is blocked and the strand is sequenced similar

to the forward strand (Illumina, 2017).

D. Alignment and Data analysis

All the sequences from pooled libraries are separated based on the indexes (barcodes) which were added to

the fragment during the library preparation. For each of the samples, forward and reverse sequences which

are sequences with similar stretches of nucleotides are locally grouped and forward and reverse sequences

are paired. This eventually, creates several contigs-sequences which are aligned back to the reference

genome in order to allow the variant identification (Illumina, 2017).

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Several methods exit in order to interpret and analyze the output from the Illumina sequencing. Sequences

are normally grouped together in clusters if they share a similarity ≥97%, which is the limit often used to

define bacterial species by 16S rRNA). A cluster is also referred to as an Operational Taxonomic Unit (OTU).

To explore the similarities or dissimilarities between samples, alpha- and beta-diversities are often used.

Alpha-diversity measures the diversity within a single sample based on the amount of different OTUs. The

beta-diversity considers the diversity between samples and is often divided into weighted or unweighted.

The unweighted beta-diversity only considers the presence or absence of species whereas the weighted beta-

diversity also considers the relative abundance of the species (Jovel et al., 2016).

Figure 2. An overview of the four steps of Illumina sequencing; A: Library preparation, B: Cluster generation/amplification, C. Sequencing and D: Alignment and data analysis. Adapted from (Illumina, 2017)

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2.3. Overview of membrane technologies

Membrane technology is a term that covers separation processes using semi-permeable membrane filters in

order to either concentrate or fractionate a liquid into two different liquids with different compositions

(Kumar et al., 2013). This is basically done by selectively allowing specific compounds to pass through the

membrane, while other compounds are retained by the membrane based on the shape and size of the

molecules in the milk (Kumar et al., 2013; Marella et al., 2013).

Membrane technology has been applied in the dairy industry since the 1960’s as an alternative to

conventional processes, such as evaporation and centrifugation (Wenten, 2016). Furthermore, the process

is a non-thermal process and thus minimizes alteration of product quality caused by high processing

temperatures, such as protein denaturation or loss of sensory attributes (Kumar et al., 2013).

When dealing with membrane filtration, terms such as feed, flux, permeate, retentate, transmembrane

pressure, fouling, concentration factor and concentration polarization are widely used. In order to

understand the mechanisms occurring during filtration process, it is necessary to understand these terms

(see Table 1).

The liquid which is going to be concentrated or fractionated is called the feed. The liquid going through the

membrane is called the permeate and the liquid retained is called retentate or concentrate. The flux defines

the rate of extraction of permeate and is measured in L/m2/h. The efficiency of the membrane is largely

given by the factor called the transmembrane pressure, which is based on the hydrostatic pressure gradients

across the membrane and the concentration gradient of the liquid (Kumar et al., 2013; Tetra Pak, 2016).

Concentration polarization occurs due to solutes accumulating on the surface of the membrane. Eventually,

the concentration of solutes on the membrane surface will be so high that the solutes will have to back diffuse

in order to equal the solutes transported to membrane surface by the flux. The consequence of concentration

polarization is reduced flux due to accumulation of solute on the membrane surface which also increases the

osmotic pressure at the surface of the membrane far beyond the level in the feed solution (APV Systems,

2000).

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Table 1. Definition of terms commonly used in membrane filtration technology (APV Systems, 2000; Kumar et al., 2013; Tetra Pak, 2016))

Feed The liquid going to be concentrated or fractionated.

Permeate The liquid permeating through the membrane

Retentate The liquid retained (also called concentrate).

Flux Defined as the rate of extraction of permeate

[L/m2/h].

Retentate concentration factor The volume reduction which is achieved during

concentration. It is given by the ratio between the

initial feed volume and the final volume

concentrate.

Transmembrane pressure The hydrostatic pressure gradients across the

membrane.

Membrane fouling Solids that irreversibly deposit on the surface of the

membrane during filtration.

Concentration polarization Accumulation of solutes causing increased osmotic

pressure at the membrane surface to increase

beyond the level of the feed solution. This reduces

the flux and the overall performance of the

membrane system

The different membrane technologies which are often associated with the dairy industry will be described in

the following section (Tetra Pak, 2016). Furthermore, Figure 3 shows a graphical comparison between the

different membrane filtrations processes.

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Figure 3. Illustrates the differences in the operating pressure, the groups of milk constituents filtrated and the membrane pore size. Adapted from Tetra Pak, (2016).

Microfiltration (MF), Ultrafiltration (UF), Nanofiltration (NF) and Reverse osmosis (RO) are the four most

widely used membrane processes used for dairy food processing. These processes differs in terms of

membrane characteristics, pore size and the operating pressure applied (Marella et al., 2013).

Microfiltration uses a membrane with a pore size varying between 0.2-2 µm and a molecular cut off above

200 KDa which allows large compounds such as bacteria, somatic cells, fat and large micellar casein from

skim milk to permeate through the membrane (Kumar et al., 2013; Marella et al., 2013).

Ultrafiltration is done by using a membrane with a pore size between 1-500 µm with a molecular weight cut

off between 1-200 KDa which allows lactose and solute salts to permeate. The filtration is run at medium

pressure 1-10 bars (Kumar et al., 2013).

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Nanofiltration is applied using a membrane with a pore size of 0.5-2 nm with a molecular weight cut off at

300-1000 Da to partially concentrate a liquid mixture. Thus, only molecules such as lactose and monovalent

salts are allowed through the membrane. During this filtration, medium to high pressure between 5-40 bar

is applied (Kumar et al., 2013)

Reverse Osmosis filtration is carried out using a semipermeable membrane to separate dissolved solutes

from, in this case, milk by allowing water to pass through the membrane (see Figure 4). The osmotic pressure

is defined by the spontaneous flow of water molecules into an aqueous solution or away from a less

concentrated solution towards a more concentrated mixture (Tetra Pak, 2016). However, for the water to

pass through the membrane, the hydrostatic pressure (indicated as “a” in Figure 4) needs to exceed the

osmotic pressure in the milk (illustrated by Phase 1 & 2 on Figure 4). This explains the high pressures between

30-60 bars that are applied in industrial applications in order to ensure a sufficient flux of water (Marella et

al., 2013; Wenten, 2016). The molecular weight cut off for the RO process is 100 Da and is carried out using

a relatively high pressure between 10-100 bar (Kumar et al., 2013).

Figure 4. Illustrates the reverse osmotic pressure mechanism which is occurring during reverse osmosis membrane filtration. Adapted from (Tetra Pak, 2016).

Various types of membranes are available on the market and are suitable for different products and

applications. In general, there are three types of membranes; flat membrane supported by frames (also

known as a plate and frame membrane), spiral-wound flat membrane (several layers of membranes

alternated with flexible supports wound around a tube) and tubular membrane (hollow supporting tubes

covered on the inside with membranes). Previously - in the 1960’s - most membranes were made from

cellulose acetate, however, nowadays membranes are made from organic polymers such as polyamides,

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polysulfones which are more resistant towards acid and alkali. For RO applications, spiral-wounded

membranes are the most commonly used configurations in dairy applications (Tang et al., 2009).

Figure 5 shows a cylindrical spiral-wound membrane system, which consists of several layers wrapped around

a perforated tube. The leaves comprise the membrane, a permeate collections side with backing up material

and a feed channel spacer (APV Systems, 2000) The feed liquid is going in from the left and is led along the

feed spacer situated between the layers of the membrane. Here the permeate is going through the

membrane into a sealed enveloped leading into the perforated tube in the middle. The retentate is led all

the way to the end of the membrane where it is collected on the outside of the membrane system.

Figure 5. Shows an overview of the composition of a spiral-wound membrane. Adapted from (APV Systems, 2000)

The membranes do not offer 100% separation of water, 99% is usually observed which means that a small

amount of substances such as sugars, minerals and ions will diffuse through the membrane (APV Systems,

2000). The pore-size of the RO membrane is smaller than 2 µm and is not detectable by common

characterization methods.

2.4. Thermal inactivation of microorganisms

Thermal inactivation of bacteria in milk concentrates is important, especially, if the concentrate is supposed

to be stored before spray drying or if it is going to be shipped to different locations. This is particularly

relevant when raw milk is the feed that enters the membrane filtration unit to avoid phycrotrophic spoilage

microorganisms proliferation during the membrane concentration process and cold storage, the potential

formation of heat resistant proteolytic and lipolytic enzymes or increased numbers of thermophilic and

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thermoduric bacteria colonizing in the equipment or formation of spores (Rasolofo et al., 2010).

Furthermore, it is important to investigate how increased dry matter and decreased water activity (aw) and

pH/salt balance of the concentrates will affect the growth and development of these microorganisms.

Studies have suggested that bacteria, in general, are more tolerant towards dry heat compared to wet heat,

which may affect the overall efficiency of the heat treatment of the concentrates (Kornacki & Marth, 1993).

One method to assess the growth kinetics of microorganisms is to determine the decimal reduction time (D-

value) and thereby determine the lethal death rate (z-value). The D-value indicates the time to inactivate

90% of the population at a given temperature and the z-value is the increase in temperature required to

obtain a ten-fold reduction in decimal reduction time (Xu et al., 2006). Generally, the population of vegetative

cells (e.g. E. coli, Salmonella spp. or L. monocytogenes) often decreases in a pattern similar to the one showed

in Figure 6 below (Singh & Heldman, 2013).

Figure 6. Shows a survivor curve for a microbial population, adapted from (Singh & Heldman, 2013)

This reduction pattern can often be described by a first-order model and expressed by the following equation

(1):

𝑑𝑁

𝑑𝑡= −𝑘𝑁 (1)

Where k indicates the rate constant and N is the reduction in the population.

When the data of the survivor curves is presented on semi log coordinates (see Figure 7), a straight line is

formed where the slope of the straight line is the first order constant (k) and is inversely related to the D-

value (Singh & Heldman, 2013).

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Figure 7. Shows two plots: Left: The microbial survivor data plotted on semi-logarithmic coordinates where D indicates the decimal reduction time. Right: The z-value. Adapted from (Singh & Heldman, 2013).

Therefore, the decimal reduction time of the survivor curve can be expressed by the following equations (2

and 3) (Singh & Heldman, 2013):

𝑙𝑜𝑔𝑁0 − log𝑁 = 𝑡

𝐷 (2)

Or

𝐷 =𝑡

𝑙𝑜𝑔𝑁0−log𝑁 (3)

The z-value can be described by the following equation 4:

𝑧 =𝑇2−𝑇1

𝑙𝑜𝑔𝐷𝑇1−𝑙𝑜𝑔𝐷𝑇2 (4)

2.4.1. Unsteady-state heat transfer and thermal inactivation experiments

The idea of this section is to provide a brief overview of some of the factors which are important to consider,

when heat inactivation studies in food products are conducted.

In this experiment, the heat inactivation of RO skim milk retentates with varying dry matter contents was

carried out in small stainless-steel cylindrical tubes specially developed for this work. One of the first aspect

to consider is the relative importance of the heat transfer at the surface of stainless-steel tube and interior

of the tube and the RO retentate sample in the tube. When the tube is heated in the heating medium, the

temperature of the tube will increase until it reaches the temperature of the heating medium. However,

during the heating, the temperature inside the stainless-steel tubes with the RO sample, the temperature

will vary with location and time. This is due to the conductive resistance of the tube and the RO sample. A

way to evaluate the impact of the convective resistance of a given object is to calculate the Biot number

(NBiot), which is defined by equation 5 and 6:

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𝑁𝐵𝑖𝑜𝑡 = 𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑙 𝑐𝑜𝑛𝑑𝑢𝑐𝑡𝑖𝑣𝑒 𝑟𝑒𝑠𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑤𝑖𝑡ℎ𝑖𝑛 𝑡ℎ𝑒 𝑏𝑜𝑑𝑦 𝑜𝑓 𝑎𝑛 𝑜𝑏𝑗𝑒𝑐𝑡

𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝑐𝑜𝑛𝑣𝑒𝑐𝑡𝑖𝑣𝑒 𝑟𝑒𝑠𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑎𝑡 𝑡ℎ𝑒 𝑠𝑢𝑟𝑓𝑎𝑐𝑒 𝑜𝑓 𝑎𝑛 𝑜𝑏𝑗𝑒𝑐𝑡 (5)

or

𝑁𝐵𝑖𝑜𝑡 =ℎ𝑑𝑐

𝑘 (6)

Where h is convective heat transfer coefficient, dc is the characteristic dimension and k is the thermal

conductivity (Singh & Heldman, 2013).

When calculating the NBiot, there are three intervals or limits which are important. A NBiot ≥40, means that the

convective resistance at the surface is much smaller than the internal conductive resistance and thus the

surface convective resistance is negligible. 0.1 ≤ NBiot ≤ 40 means that there is a finite internal and external

resistance to heat transfer. NBiot ≤ 0.1 means that the internal resistance to heat transfer can be negligible.

This mean that the temperature development inside the tube containing the RO sample can be considered

uniform. This is also referred to as a “lump system” (Singh & Heldman, 2013).

Heating of such a system can be evaluated based on following equation (7):

𝑇𝑎−𝑇

𝑇𝑎− 𝑇𝑖= 𝑒

(−−ℎ∗𝐴∗𝑡

𝜌∗𝐶𝑝∗𝑉) (7)

Where, Ta is the desired heating temperature, Ti is the initial temperature of the object, T is the temperature

at a given time, h is convective heat transfer coefficient, A is the area of the object receiving the heat transfer,

ρ is the density of the object, Cp is the specific heat coefficient and V is the volume of the object (Singh &

Heldman, 2013).

2.5. Literature review on microbiological and milk aspects during membrane filtration

The aim of this section is to provide a more detailed overview of the application of membrane filtration, with

focus on reverse osmosis, in the dairy industry as well as of its possibilities and limitations.

The most common application of RO is for concentrating whey as well as concentrating permeate received

after UF of whey. However, the feasibility of concentrating milk by RO prior to cheese, yoghurt or milk powder

production has also been investigated (Barbano & Bynum, 1984; Kumar et al., 2013; Kumarkaw, 1998).

Furthermore, several studies have been conducted on water reclamation from waste water (Wenten, 2016).

In the 1980’s, two studies were carried out dealing with whole milk concentrates made using RO for cheddar

production (Agbevavi et al., 1983; Barbano & Bynum, 1984). Agbevavi et al., (1983) found that cheddar

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cheese made from 2-fold concentrated whole milk required 50% less starter culture as well as 60% less rennet

compared to conventional cheddar cheese made from unconcentrated whole milk. Barbano & Bynum (1984)

investigated cheddar cheese made in a conventional cheese factory with whole milk concentrates which were

reduced in volume 5%, 10%, 15% and 20% using RO. Despite the higher lactose content in the concentrated

milk, it did not affect the proteolysis during the first 3 months of ripening compared to the conventional

cheddar cheese (Kumarkaw, 1998). Additionally, Barbano & Bynum (1984) found an increase in cheese yield

of 2% to 3% above the expected theoretical yield when using the whole milk which was reduced by 20% in

volume (Barbano & Bynum, 1984).

A study in India aimed at investigating the feasibility of preconcentrating buffalo milk from chilling centers

located in rural areas before transporting the milk into the dairy factories in the cities (Gupta & Pal, 1993;

Kumarkaw, 1998). The milk concentrated either 1.5-fold or 2-fold by RO was stored at 4oC and occasionally,

shaken in order to simulate the typical unsteady transportation conditions (Gupta & Pal, 1993). The study

found that the organoleptic quality of fresh RO concentrated milk as well as reconstituted RO milk was

identical with the conventional buffalo milk (Gupta & Pal, 1993; Kumarkaw, 1998). RO milk stored for 72 h at

5oC were observed without any flavor changes, and, only slight increases in free fatty acids, titrable acidity

and microbial count were seen. Eventually, the energy consumptions for the 1.5-fold and 2-fold

concentrations using the RO filtration were calculated to be 369.7 and 470.9 KJ/Kg of water removed

respectively (Gupta & Pal, 1993; Kumarkaw, 1998). The chilling facility located 300 km away from the main

city dairy, was handling 10,000 L milk/day. Performing 50% in volume reduction on the buffalo milk, the

estimated cost savings were approx. 25%. This meant that the time for return of the investment period on

the application would be approx. one year (Gupta & Pal, 1993; Kumarkaw, 1998).

Both Abbot et al., (1974) and Dixon (1985) investigated the possibility of using reverse osmosis as an

alternative to traditional evaporation prior to spray drying. Both concentrated whole milk and skim milk

containing 30% dry matter content were suitable concentrates ready for spray-drying or for direct production

of evaporated milk products (Abbot et al., 1974). This was also supported by Dixon (1985), who found that

conventional evaporation steps could be replaced by using RO filtrated skim milk in milk powder production

(Dixon, 1985). Furthermore, RO filtration also allows for less heat damage as well as less denaturation of milk

proteins compared to conventional evaporation (Twiford, 2004).

However, RO and other membrane technologies do have limitations. The major limitation is the reduction in

flux during the filtration process also known as concentration polarization or fouling of the membrane (El-

gazzar & Marth, 1991; Kumar et al., 2013). This phenomenon occurs when, for instance, milk solids deposit

irreversibly to the surface of the membrane limiting the cross-flow during the filtration process (El-gazzar &

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Marth, 1991; Kumar et al., 2013). In order to remove the deposit, thorough cleaning is often necesscary,

which explains the extensive research being done towards finding new solutions to limit both the fouling of

the membrane but also optimization of the cleaning procedures reducing the “down-time” and extending

the production-time (Kumar et al., 2013).

Sørensen et al., (2015) investigated the potential impact of the RO filtrations process on the milk quality in

regards to proteolysis and lipolysis. Even though, the RO process is using higher pressure compared to UF,

the contribution to the lipolysis was found to be small. It was suggested that the low operating temperatures

were likely to compensate for the mechanical stress during the high pressure pumping and filtration process.

The final conclusion was that concentrating milk using RO membrane filtration is possible and does not cause

any severe changes to the milk quality (Sørensen et al., 2015).

Currently, there is relatively few studies carried out in order to investigate aspects such as the microflora of

milk retentates as well as microbial growth and spoilage of these. However, one study carried out by Tang et

al., (2009) investigated factors affecting the attachment of microorganisms isolated from both UF and RO

membrane dairy processing plants after cleaning. Cell surface characteristics such as cell hydrofobicity and

charge are generally believed to be important factors influencing the ability of microorganisms to attach to

different surfaces. However, this study did not find any clear relations between these factors and the

attachment of the bacteria which were isolated. However, the variety of microorganisms isolated from the

membrane plants was suggested to be a consequence of inadequate cleaning (Tang et al., 2009).

Some studies have been carried out investigating the thermal destruction of specific bacterial strains in other

milk concentrates such as ultra-filtrated and diafiltrated milk concentrates (Kornacki & Marth, 1993).

Troller (1986) stated that salmonella and staphylococci became more heat resistant as the aw decreased.

However, this was only the case until the aw reaches a value between 0.70 and 0.80, then the heat resistance

seemed to decrease. Kornacki et al., (1993) did not see any significant differences in D- and z-values for M.

freudenreichii in unconcentrated skim milk and ultra-filtrated skim milk retentate (3.5X) when it was heated

at 63oC, 68oC and 73oC. The skim milk was heated in 2 min, 0.18 min, 0,086 min and 0.022 min and the

retentate was heated for 2.1 min, 0.21 min and 0,063 min (Kornacki & Marth, 1993). However, Kornacki et

al., (1993) suggested that the thermal resistance of microorganisms in the milk may be connected to the

amount of one or more low molecular weight solutes present in the milk including the colligative properties

of the milk solution. This may explain the lack of a significant difference between D- and z-values for

unconcentrated skim milk and UF skim milk retentate. Because, even though the dry matter content

increases during UF, the osmolarity remain fairly unchanged (Kornacki & Marth, 1993). Contrary to ultra-

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filtrated skim milk, the osmolarity will increase for RO milk retentates since all solutes are being concentrated

during reverse osmosis (Kornacki & Marth, 1993).

Dega et al., (1972) investigated the influence of various skim milk solids and temperature on the duration of

lag phase, growth and extent of growth of S. typhimurium. Furthermore, the effect on growth during reduced

pressure at constant solids levels and conditions simulating condensation of skim milk under vacuum was

also investigated (Dega et al., 1972). Total solids levels at 10%, 30%, 40%, 50% and 60% and incubation

temperatures at 10-12oC, 23oC, 32oC, 37oC and 44oC were applied (Dega et al., 1972). The study found that

when the total solids increased (especially at 50-60%), or the incubation temperature deviated from the

optimum of S. typhimurium, the lag phase and the generation time increased resulting in a reduced

population of cells (Dega et al., 1972).

Barbano & Bynum, (1984) investigated the use of whole milk RO retentates (0%, 10%, 15% and 20% volume

reduction, containing 11.89%, 12.88%, 13.27%, 14.17% and 15,05% milk solids, respectively) in cheddar

cheese manufacture and it was concluded that cheddar cheese made from 15% and 20% volume reduced

retentates required 20% to 30% less inoculum of the starter culture (Barbano & Bynum, 1984).

3. Materials and methods

3.1. UF samples from Slagelse dairy

Samples of the UF retentate were collected in sterile containers approximately 30 min. inside the production

and 30 min before the end of the production. The retentate was thermized at 65oC for 15 s. after the filtration

process. The samples were placed on ice and transported to UCPH, where they were analyzed. This was done

for approximately two weeks. Since the UF concentrates was thermized after filtration, plating on agar was

only done for the two samples from the first UF production. Illumina sequencing was performed for all the

samples.

3.1.1. Cell harvest for DNA preparation

10g of UF sample was transferred to a sterile stomacher bag along with 90g of sterile 2% trisodium citrate

and mixed in the stomacher machine for 30 seconds at medium speed. This was done to precipitate the

casein and thereby releasing the bacteria so they were available in the serum phase. At this point the UF

sample was diluted into 10-1 dilution. 40 mL of 10-1 dilution was transferred into two sterile falcon tubes. The

tubes were centrifuged (Allegra™ 25R Centrifuge, Beckmann Coulter Inc., IN, USA) 300*g for 15 min.. 20 mL

of supernatant was transferred into two sterile falcon tubes and centrifuged at 5000*g for 15 min.. The

supernatant was removed from each tube and the pellets were resuspended in 1 mL of sterile 0.9% (w/v)

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Sodium Chloride (NaCl)-solution and transferred to Eppendorf tubes and centrifuged (Hermle centrifuge Z

216 MK, Hermle LaborTechnik, Wehingen, Germany) at 15,000*g for 2 min. The supernatant was removed

and the pellet stored at -20oC.

3.2. RO samples from Arinco dairy and production trials at UCPH

At Arinco dairy, the reverse osmosis filtration process was carried out at approx. 9-11oC and the pasteurized

skim milk was concentrated to brix 29o and 25% dry matter. The final RO concentrate was not heat treated

after concentration and the sampling was done aseptically using sterile needles and syringes.

3.2.1. Cell harvest for DNA preparation

The cell harvest procedure was similar to the one applied for the UF samples but this step was carried out in

the laboratory facilities at Arinco dairy (Arla Foods, Videbæk, Denmark). Additionally, dilution rows (10-1 to

10-3) were made for each sample using 0.9% (w/v) NaCl-solution. From each dilution 100 µl was transferred

onto a Petri dish containing Plate Count Agar (PCA) (Oxoid ltd., ThermoFischer Scientific, Waltham, MA, USA)

with 1% (v/v) added sterile organic skim milk obtained from the local grocery store. The final dilution factor

on the plate was thus 10-2 to 10-4.

3.3. InstaGene DNA extraction for Rep-PCR and 16s rRNA sequencing

A total of 42 isolates were randomly selected from a plate containing the “end”-plates from day 1 and pure

cultures were made by streaking the single colonies onto fresh PCA and incubated three days at 30°C.

From the pure cultures, a colony was transferred to a microfuge tube and resuspended in 1 mL of autoclaved

MilliQ-water. The samples were centrifuged for 1 min. at 12,000 rpm and the supernatant subsequently

discarded.

The remaining pellet was resuspended in 100 μL of InstaGene matrix (Bio-Rad Laboratories, Hercules, C, USA)

and incubated at 56°C for 30 min.. Afterwards the samples were vortexed at high speed for 10 s and placed

in a 100°C heating block for additional 8 min.. After incubation, the samples were vortexed at high speed for

10 seconds and subsequently spun at 12,000 rpm for 3 min.. The supernatant (the extracted DNA) was

transferred into new Eppendorf tubes and stored at -20°C.

3.4. Repetitive Sequenced-Based PCR (rep-PCR)

The rep-PCR mixture was prepared by adding PCR-mastermix, primers (GTG5, 5µM 5’-GTGGTGGTGGTGGTG-

3’) (Integated DNA Technologies, Iowa, USA) and sterile MilliQ-water to an Eppendorf tube. Table 2 shows

the amount each component required per PCR reaction.

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Table 2. Volume of each component required for one PCR reaction in rep-PCR.

Compound Volume per reaction (µl)

PCR Mastermix 13

Primer (GTG5 5µM) 5

Sterile MilliQ-water 4

Sub-total 22

DNA sample 3

Total 25

The appropriate volume of rep-PCR mixture was obtained by the number of reactions (number of DNA

samples) plus two additional reactions (e.g. in case of 8 DNA samples + 2 = 10 reactions). Once the PCR-

mixture had been prepared, 22 µl were added to a PCR tube along with 3 µl of DNA sample. A blank (without

DNA) sample was also prepared where 3 µl of sterile MilliQ-water were added instead of DNA sample.

After mixing, the samples were placed in a thermocycler (Agilent SureCycler 8800, Santa Clara, CA, USA) and

the following program was applied (see Table 3)

Table 3. Thermocycler program for rep-PCR

Temperature [oC] Time

Initial 95 5 min.

Denaturation 95 30 s.

30 cycles Annealing 45 60 s.

Elongation 65 8 min.

Extension 65 16 min.

Storage 4 ∞

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After the thermocycling, the PCR-products were ready to be separated using agarose gel electrophoresis. An

1.5% agarose gel was prepared with 0.5X TBE buffer (10X TBE: 108g Trizma base (Sigma-Aldrich), 55g boric

acid (Sigma-Aldrich) and 7.4g NaEDTA•H2O (372.2 mol) (Sigma-Aldrich)) and the running chamber was also

filled. 10µl of sample were loaded into each of the wells in the gel and in every 8th well, 3µl of marker (1K bp)

(ThermoFischer) were loaded. The gel electrophoresis was run at 120V for 2.5h.

Eventually, the gel was stained with ethidium bromide and photographed in a UV-light chamber (Alpha

Innotech, Kasendorf, Germany) using the software AlphaImager (Alpha Innotech).

Based on the picture of the gel, groups of band patterns were identified and as a minimum, the square root

of the number of isolates in each of the groups were selected for 16S rRNA gene sequencing.

3.5. Amplification and sequencing of the 16S rRNA gene

The PCR-mixture was prepared by mixing PCR mastermix (TermoFischer), Primer mix (16S-27F (5’-

AGAGTTTGATCMTGGCTCAG-3’) and 16S-1540R (5’-TACGGYTACCTTGTTACGACT-3’) (5µl) (Intergated DNA

Technologies) and MilliQ-water. Table 4 below shows the volume of each component required for one PCR

reaction (sample).

Table 4. Volume of each component required for one PCR reaction in 16S rRNA gene amplification

Compound Volume per reaction [µl]

PCR mastermix 25

Primer (16s-27F and 1540R) 5

Sterile MilliQ-water 17

Sub-total 47

DNA sample 3

Total 50

47µl of the mixtures were added to PCR tubes and subsequently 3µl DNA sample were added. A blank sample

was included where 3µl of sterile MilliQ-water were added instead of DNA. Afterwards the samples were

placed in the thermocycler (Agilent) and the following program was applied (see Table 5).

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Table 5. Thermocycle program used in 16S rRNA gene amplification.


Initial 95 5 min.


30 cycles Annealing 60 30 s

Elongation 72 2 min.

Extension 72 10 min.

Storage 4 ∞

In order to separate the PCR products, a 1.5% agarose gel was prepared with 0.5X TBE buffer (10X TBE: 108g

Trizma base (Sigma-Aldrich), 55g boric acid (Sigma-Aldrich) and 7.4g NaEDTA•H2O (372.2 mol) (Sigma-

Aldrich)) and the running chamber filled with 0.5X TBE-buffer. 5µl of sample was loaded into the wells in the

gel and 3µl of 100 bp marker (ThermoFischer) were added to the first and last well. The electrophoresis was

run at 120V for 30 min and eventually, the gel was stained with ethidium bromide and photographed in a

UV-light chamber (Alpha Innotech).

Afterwards, the samples were sequenced using forward-primer 27F (5’-AGAGTTTGATCMTGGCTCAG-‘3)

and either 800R (5’-TACCAGGGTATCTAATCC-‘3) or 907R (5’-CCGTCAATTCMTTTRAGTTT-‘3) as reverse-

primers at Macrogen (Macrogen Europe, Amsterdam, Netherlands).

All sequences were manually corrected and assembled using the software CLC Main Workbech 6.0 (Aarhus,

Denmark). Subsequently the sequences were compared to sequences available in the GenBank databases by

using the BLAST (Basic Local Alignment Search Tool) function at the NCBI Webpage:

https://blast.ncbi.nlm.nih.gov/Blast.cgi.

3.6. Gram-test and catalase-test

All isolates which were selected for 16S rRNA gene sequencing were also Gram-stained and catalase-tested

in order to support the results from the BLAST search.

The Gram-test was performed by placing a drop of 3% KOH on a microscope slide and subsequently

transferring a loop full of cell material onto the drop with a sterile needle. If the slimy threads appeared when

https://blast.ncbi.nlm.nih.gov/Blast.cgi

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the needle left the liquid, the cells were considered Gram-negative and if the slimy threads did not appear,

the cells were Gram-positive.

A catalase-test was performed by adding a drop of 3% hydrogen peroxide (H2O2) on a microscope slide and

subsequently adding a loop full of cell material to the drop. If the bacteria possessed the catalase enzymes,

the hydrogen peroxide would be split into water and oxygen (see equation below).

𝐻2𝑂2 𝐶𝑎𝑡𝑎𝑙𝑎𝑠𝑒→ 2𝐻2𝑂 + 𝑂2 (8)

Therefore, a catalase-positive reaction would generate small air bubbles inside the drop.

3.7. Illumina sample preparation procedure

The Illumina sample preparation procedure was carried out according to the laboratory manual made by

Greppi (2016).

3.7.1. Extraction of DNA for Illumina sequencing

Prior to the Illumina sequencing procedure, DNA from the frozen pellets, from all the UF and RO samples,

was extracted using the PowerSoil® DNA Isolation Kit (MoBio Laboratories Inc, QIAGEN, USA). The following

procedure was applied to all samples.

The pellet was thawed and resuspended in sterile 0.9% NaCl-solution and transferred to a PowerSoil Bead

Tube, vortexed and incubated at 65oC for 10 min. and subsequently 95oC for another 10 min.. After heating,

60µl of solution C1 were added to the tube and placed in a FastPrep®-24 ClassicK instrument (MP

Biomedicals, CA, USA) receiving 3 cycles of homogenization (15s at 6.5 M/s.).

The PowerSoil Bead Tube was centrifuged at 10.000*g for 30s and the supernatant transferred to a clean

Eppendorf tube. Solution C2 was added to the sample, briefly vortexed and incubated at 4oC for 5 min.. The

sample was subsequently centrifuged at 10.000*g for 1 min. and 600µl of the supernatant transferred to a

clean Eppendorf tube to which 200 µl of Solution C3 were added and incubated at 4oC for additional 5 min.

The sample was centrifuged at 10.000*g for 2 min. and 750µl of the supernatant were transferred to clean

Eppendorf tube together with 1200µl of Solution C4.

650µl of the mix was loaded into an Eppendorf tube containing a Spin Filter and centrifuged at 10.000*g for

1 min. whereby the flow through was discarded. Additional 650µl of mix were loaded into the filter and

centrifuged at 10.000*g for 1 min. and the flow through discarded. 500µl of Solution C5 was added to the

filter and the centrifuged at 10.000*g for 30s.

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Subsequently, the filter was carefully transferred to a clean Eppendorf tube (collecting tube) and 100µl of

Solution C6 were added to the center of the white filter membrane and centrifuged at 10.000*g for 30 s..

Eventually the filter was discarded and the flow through (extracted DNA sample) stored at -20oC until further

use.

Before preparing the Illumina sample, the DNA concentration was measured on the extracted DNA samples

(MoBio Kit). This was done by placing 1-2µl of DNA sample onto a NanoDrop™ Spectrophotometer (Thermo

Scientific, ThermoFischer Scientific Inc., Waltham, MA, USA) which uses the absorbance at 260 nm to

calculate the DNA concentration. Based on the DNA concentration of the samples, the individual sample

concentration was normalized to contain maximum 10ng/µl and samples with DNA concentrations below

10ng/µl were used without further adjustment. This was done in order to ensure optimal conditions for the

primers used later in the process.

3.7.2. Assembling the 1st PCR (amplification of the V3 region of 16s rRNA):

The first PCR reaction was carried out by preparing a mastermix containing the AccuPrime SuperMix II

(Thermo Scientific), the PrimerMix comprising the forward-primer NXt-388 and the reverse-primer NXt-518

(each having a concentration of 10µM) (Illumina, San Diego, USA) and sterile water. Table 6 shows the

composition and the function of the primers.

Table 6. Primers specific for the V3 region of 16s rRNA gene. Green and orange colors indicate the adapter-sequences needed for 2nd PCR reaction, red indicates the primer sequence specific for the V3 region of the 16S rRNA gene and blue color represents the sequence connecting the adapters for 2nd PCR and the V3 primer sequence together.

Primer Primer sequence 5’-3’

NXt-388_F TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGACWCCTACGGGWGGCAGCAG

NXt_518_R GTCTCGTGGGCTCGG AGATGTGTATAAGAGACAG ATTACCGCGGCTGCTGG

Green and orange: Adapters

which are needed for the 2nd

PCR reactions

Red: Primer sequence for the V3

region of the 16S rRNA gene.

Blue: Sequence connecting the

adapters for 2nd PCR and the specific

primer sequence

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Table 7 below shows the volume of each reagent required per DNA sample.

Table 7. Volume of each component required for one PCR reaction in the 1st PCR run.

Reagent Volume per sample [µl]

AccuPrime SuperMix II 12

PrimerMix (NXI_388_F & NXt_518_R (10µM each)) 1

H2O 7

DNA sample (1-10ng/µl) 5

20µl of mastermix were added to the PCR tube along with 5µl of DNA sample and subsequently placed in the

thermocycler (Agilent) with the following temperature profile applied (see Table 8).

Table 8. Thermocycle program used in 1st PCR run

The PCR product was seperated using gel eletrophoresis. A 1.5% agarose gel was prepared with 0.5X TBE

buffer (10X TBE: 108g Trizma base (Sigma-Aldrich), 55g boric acid (Sigma-Aldrich) and 7.44g NaEDTA•H2O

(372.2 mol) (Sigma-Aldrich)) and the gel electrophoresis running chamber was filled with 0.5X TBE-buffer.

The gel was run for approximately 30 min at 110V. The expected size of the PCR product was 190 bp. If good

amplification and PCR products of 190 base pairs were achieved and the control sample (with no DNA added)

was negative, then the 2nd PCR could be conducted.


Initial 95 2 min.



Elongation 68 30 s.

Extension 68 4 min.

Storage 4 ∞

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3.7.3. 2nd PCR (barcoding of the amplified samples for sequencing)

The mastermix for the 2nd PCR reaction was prepared by mixing PhusionHF mix (ThermoFischer) and sterile

water. Table 9 below shows the volume of each reagent required per sample.

Table 9. Volume of each component required for one PCR reaction in the 2nd PCR run

Reagent Volume per sample [µl]

PhusionHF mix 12

Primer 1 2

Primer 2 2

H2O 7

1st PCR product 2

19µl of the mastermix were added to the PCR tube along with 2µl of PCR 1 product. Afterwards, every sample

was added a unique combination of primers (Illumina). Thus, the sequences from each of the individual

samples would be provided with a unique barcode. This would allow the samples to be recognized and sorted

according to barcodes after sequencing.

Figure 8 shows positioning of the different barcode-primers as they were added to the respective samples.

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Figure 8. Shows how the different barcode-primers were organized before they were added to the samples. Adapted from (New England BioLabs, 2017).

Table 10 shows two examples of the composition of the primers providing the unique barcodes. An overview,

showing the primer set-up providing the samples with unique barcodes can be found in Appendix, section 5.

Table 10. Examples showing the composition of the primers providing the unique barcodes. Green and Orange indicate the area of the primer which attach to the 1st PCR products, the red color indicates the unique barcodes and the black sequence defines the area that binds to the flow disc during bridge amplification

Primer Primer sequence 5’-3’

S501 AATGATACGGCGACCACCGAGATCTACACTAGATCGCTCGTCGGCAGCGTC

N701 CAAGCAGAAGACGGCATACGAGATTCGCCTTA GTCTCGTGGGTCGG

Green and orange: Adapters which attach

to the 1st PCR products

Red: Primer barcodes Black: Primers which attach to the

bridge amplification slide.

After mixing mastermix, primers and the PCR 1 product, the samples were placed in a thermocycler (Agilent)

and the following temperature profile was applied (see Table 11).

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Table 11. Thermocycle program applied during 2nd PCR.

After the temperature program, the next step was cleaning.

3.7.4. Cleaning of library (PCR amplicons)

The principle of the cleaning step was to purify the PCR amplicon library using Agentcourt AMPure XP beads

system (Beckman Coulter Inc.). These beads provides purification of the the PCR amplicon and removal of

very small DNA fragments, such as primer dimers, dNTPs and primers. The cleaning step was performed using

a Biomek® 4000 Workstation (Beckman Coulter Inc.).

The process consisted of six steps as illustrated on Figure 9. First the AMPure XP beads (Beckman Coulter

Inc.) were vortexed in order to ensure that the mix was evenly in solution. Thus 20µl of the mix were added

to the individual PCR 2 products, gently mixed by pipetting up and down ten times and incubated at room

temperature for 5 min. After the AMPure XP beads (Beckman Coulter Inc.) had bound to the desired PCR

amplicons, the samples were placed on a magnetic stand in order for the PCR amplicons to percipitate leaving

the unwanted DNA fragments in the supernatant. Thus, the supernatants were carefully removed and

discarded.

Subsequently, the samples were washed with 200µl of freshly prepared 80% (v/v) Ethanol, incubated on the

magnetic stand at room temperature for 30 s. and the supernatant discarded. This step was repeated one

more time and the samples were left on the magnetic stand (ThermoFischer) in order to dry for 15 min.


Initial 95 2 min.



Elongation 68 20 s.

Extension 68 5 min.

Storage 4 ∞

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The samples were removed from the magnetic stand and 27µl of elution buffer (MN buffer, 5mM Tris/HCL,

pH 8.5) (QIAGEN) were added to the samples and gently mixed ten times in order for the PCR amplicons to

detach from the AMPure XP beads (Beckman Coulter Inc.). The samples were incubated at room temperature

for 2 min. and placed back onto the magnetic stand for another 2 min. until the supernatants had cleared.

At this point, the samples were cleaned and 25µl of supernatant from each samples were transferred to

another clean amplified NTA plate.

Figure 9. 1. PCR reaction 2. Binding of PCR amplicons to magnetic beads 3. Separation of PCR amplicons bound to magnetic beads from contaminants 4. Washing of PCR amplicons with Ethanol 5. Elution of PCR amplicons from the magnetic particles 6. Transfer away from the beads into a new plate. Adapted from (Beckmann Coulter, 2017)

3.7.5. Measuring the concentration of the purified library

The last step was to measure the concentration of the purified library, in order to determine the amount of

each sample that had to be transferred to the final tube and sent for sequencing.

This was done using the Qubit™ Assay Kit (ThermoFischer). First, the working solution was prepared by mixing

99.5µl of dsDNA HS Buffer with 0.5µl of dsDNA reagent per number of samples + two extra samples in case

of pipetting error.

98µl of the mix were added to the wells in a microtiter plate followed by 2µl of purified PCR product samples.

One well was added 95µl of mix along with 5µl of HS standard 1 (ThermoFischer) and 95µl of mix was added

to a second well along with 5µl of HS standard 2 (ThermoFischer). The microtiter plate was placed in a

Varioskan (ThermoFischer) using the predefined “nextera_library_qubit”-template in Microsoft Excel. Based

on the results, the DNA concentrations were calculated as well as the amount of each sample needed when

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pooling the samples in the final Eppendorf tube. At this point, the samples were ready to be sent for

sequencing.

3.8. Production of RO milk concentrate/retentate

Raw skim milk from Slagelse dairy (Arla Foods, Denmark) was concentrated by reverse osmosis (RO) on pilot

scale in the pilot plant at Universisty of Copenhagen, (Frederiksberg C, Denmark). The concentration process

was carried out at 8-11oC at a transmembrane pressure between 5-36 bars in order to obtain dry matter

contents of approximately 15%, 20%, 25% and 30%. Once the concentrates had been collected, they were

stored at -20oC until further use. A flow sheet of the filtration unit and an illustration of the unit are shown

in Figure 10 and Figure 11.

Figure 10. Shows an overview of the RO membrane filtration unit (GEA) used for the trials carried out at UCPH.

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3.8.1. Operating procedures and preparations of the RO pilot unit

Prior to operation, the membrane in the RO unit was replaced with a new membrane (Dairy-Pro™ RO

Element, SPIRAL,3838-RO-30, Koch Membrane Systems Inc., Wilmington, MA, USA). A Cleaning-In-Place (CIP)

program was performed both in order to clean the RO system but also to ensure that conservation fluid

(glycerol) from the new membrane was removed before adding milk to the system. The CIP program was

conducted by recirculating hot demineralized water in the RO system until system reached 50oC. Afterwards,

approximately 1.5ml of alkali (P3 Ultrasil 110) (Ecolab, St. Paul, MN, USA) was added to the balance tank to

obtain pH 10 and recirculated for 800s. Subsequently, the system was flushed and rinsed with hot

demineralized water until neutral pH was reached and approximately 1.5 ml of acid (P3 ultrasil 110) (Eolab)

to secure pH 3 followed by addition 800s of recirculation. Finally, the system was flushed and rinsed with

cold demineralized water. Since the unit was not going to be used immediately afterwards, approximately

1ml of acid (P3 ultrasil 110) (Eolab) was added to the system after cleaning adjusting pH down to 4 for

conserving the membrane, preventing bacterial growth and limiting biofilm formation.

Before every production, the system was CIP cleaned again starting, however, with the acidic wash followed

by the alkaline wash and final rinse. This would limit the risk of milk coagulating in the system if the pH was

not neutral throughout the system.

Figure 11. Shows a complete drawing of the membrane filtration unit, which was used production of RO concentrates at UCPH, Adapted from (Sørensen, 2017)

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Following production, an additional CIP was performed. However, approximately 1ml of acid (P3 ultrasil 110)

(Eolab) was eventually added to the system to obtain pH 3 conserving the system until next production.

3.8.2. Production

The concentration process was started by activating the “Produkt Tilstand” and “RO Drift” on the control

screen. Once activated, the buttons turn green. In order to start the automatic flow control, the “RO1Flow”

was activated. The concentrations factor was entered into the top yellow box (see Figure 12).

Figure 12. Picture taken of the control screen controlling the pilot RO filtration unit at UCPH.

The feed pressure was entered in the bottom yellow box and set to 5 bars at startup. During the

concentration process the feed pressure was increased with 5 bars until 25 bars was reached. When

operating above 25 bars, the pressure was increased or decreased in 2 bars intervals. Sufficient time between

adjusting the feed pressure should allow the pressure and the feed flow rate to stabilize.

The unit was equipped with three pumps and the starting sequence of these was first the feed pump

(F03GF01) followed by the high-pressure pump (F03GF02) and eventually the loop pump (L01GF01) and the

pump. Shutting down the pumps was done in the reverse order.

The concentration process started out as a continuous filtration meaning that both permeate and retentate

were removed from the system. This was done in order to ensure sufficient replacement of water from the

unit after startup.

Once the dry matter reached 15% or the first 100L of milk was used, the permeate was led to the drain and

the retentate back into the system thus creating a batch filtration process. The dry matter content was

measured on a MilkoScan (Foss, Hillerød, Denmark) and the Brix value on a handheld brix refractometer

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(ATAGO CO LTD, Tokyo, Japan) during the filtration process in order to obtain an indication of the actual dry

matter content. The actual dry matter content was determined is describe in the following section.

Once the dry matter content had reached 15%, 20%, 25% and 30% both permeate and retentate were

recycled in the system in order to achieve a steady-state concentration. After a few minutes of recycling, the

samples were collected and stored at -20oC until further analysis.

At the end of the concentration process, the system was flushed by adding demineralized water to the

balance tank and removing the permeate and retentate from the system. As the high-pressure pump

increased in rounds per minute (RPM), the feed pump pressure was reduced in intervals down to 5 bars,

similar to the start-up procedure. After this, the pumps were restarted, valves for the high-pressure pump

and the loop pump were placed in a 45o angle in order to create bypass flow. Once clear water was coming

out of the permeate and retentate hoses, the pumps were shut down and the “CIP Tilstand” was activated.

The pumps were restarted and the CIP program carried out as previously described.

3.9. Determination of total solids content

Approximately two grams of milk/concentrate was added to a beaker with dried clean pumice and placed in

an oven over-night. The sample was dried at constant temperature (100±2oC) until a constant weight was

achieved. Afterwards, the sample was transferred to a desiccator and cooled at room temperature before it

was weighted again. The total solids content (%) was calculated using the equation (9) below:

𝑇𝑆 = 𝑚2− 𝑚0

𝑚1− 𝑚0∗ 100% (9)

where m0 is the mass of the beaker and pumice before adding the milk sample, m1 is the mass of the beaker,

pumice and milk sample before drying and m2 is the mass after drying.

3.10. Thermal inactivation of M. lacticum in RO skim milk concentrate

3.10.1. Preparation

The frozen RO concentrates were placed in a fridge at 4oC and the following day the concentrates were stored

on ice throughout the experiment. An over-night (ON) culture was prepared by adding a colony of each pure

culture of M. lacticum (isolate 103 and 112) to approximately 100 ml of organic skim milk pre-cooked for 30

min. The ON culture was incubated over-night at 30oC. Both isolates were determined to be M. lacticum

based on 16S rRNA gene sequence BLAST results (see 4.4 Heat-inactivation of M. lacticum in raw RO skim

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milk retentates). Since the isolates had different pigmented colonies, it was decided to add both isolates

during the thermal inactivation experiments.

Small stainless-steel tubes with fittings made of brass mounted at each of the ends were produced by the

mechanical workshop at University of Copenhagen (Figure 13). Specification of the tube are listed in Table

12.

Table 12. Specifications of the tubes used for the thermal inactivation experiments.

Tube specifications

Diameter Inner: 4mm / outer 6mm

Height 7.9cm

Area 0,001m2

Volume 1.005*106 m3

Material (tube/fittings) Stainless-steel/Brass

3.10.2. Experiment

The inactivation experiment was carried out on raw milk and skim milk concentrates containing 15%, 20%,

25% and 30% DM and all heated at 57oC, 62oC, 67oC and 72oC for times of 0s, 30s, 60s, 120s and 180s. For

each temperature, heating trials were carried out twice with two individual replicates per milk/concentrate

for each heating time. An overview of the experimental set-up is provided in Figure 14.

On the day of the experiment, cells from the ON culture were harvested. This was done by transferring the

ON culture into a stomacher bag together with 100ml of sterile 20% (w/v) tri sodium citrate followed by 30

secs of medium mixing. Afterwards 40ml of the mixture were transferred into a sterile blue-cap and

centrifuged (Beckman Coulter Inc.) at 300*g for 15 min. Subsequently, 20ml supernatant were collected and

transferred into a new blue-cap and centrifuged (Beckman Coulter Inc.) at 5000*g for additional 15 min. The

supernatant was removed and the pellet was resuspended in 1 ml of sterile 0.9% (w/v) NaCl-solution and

transferred to the approximately 20ml of concentrate sample. For each experiment, one ON culture was

prepared. The ON culture was divided into blue-caps according to the number of concentrates which were

heated. Thereby individual pellets were generated in order to ensure as high inoculum as possible to each

concentrate sample.

Figure 13. Picture of one of the tubes used in the thermal inactivation study.

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After addition of the inoculum, the respective concentrates were transferred into the stainless-steel tubes

using sterile Pasteur pipettes and the fittings sealed.

The tubes were placed in large racks leaving sufficient space between the tubes to allow optimal heating.

One rack was put in the water bath (Grant W28, Grant Instruments, Cambridge, UK.) at a time and the timer

(Iphone, Apple, CA, USA) was started once the tubes were completely covered by the water. The water in the

water bath was heated by a Julabo ED heating module (Julabo ED, Seelbach, Gernmany) with incorporated

circulator. The temperature was measured using a digital thermometer (Multi). After each heat treatment,

the tubes were immediately transferred to ice-water and cooled for at least 10 min.

Figure 14. Illustrating the setup during the heat inactivation of RO samples. To the left is the heated water-bath including the heating coil, thermometer, agitator and the tubes which are being heated. To the right is the ice-water bath used to rapidly cool down the tubes immediately after the heating.

After heating, approximately 100µl of sample from each tube were transferred to a sterile microtiter plate.

Here serial dilutions to 10-6 were made and 5µl from each dilution was put on a 10 X 120mm square 1% milk

PCA agar plate. The agar plates were incubated for three days at 30oC and growth of the surviving bacteria

was noted.

Eventually, the growth data of M. lacticum was plotted on semi-logarithmic coordinates allowing for D- and

z-values to be calculated.

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4. Results and discussion

The aims of this study were to investigate the microflora of raw and heat-treated UF concentrate, and RO

skim milk retentates. Furthermore, the microorganisms which were growing in the retentates were isolated

and identified. Based on these results, specific microorganisms were selected for a heat-inactivation study.

The purpose of the heat-inactivation study was to investigate the thermal inactivation of selected

microorganisms including the potential influence of the dry matter content and temperature in the

retentates.

The purpose of this section is therefore to layout, analyze and discus these results. The section is divided into

two main parts; the results from the identification of microorganisms in UF milk and the results from the

identification and inactivation of microorganisms in RO concentrated milk.

4.1. Ultra-filtrated concentrate

4.1.1. Illumina results based on DNA from 38 UF-sample collected at Slagelse dairy

A total of 38 samples of extracted and prepared DNA from UF retentates from Slagelse dairy were analyzed

using Illumina sequencing. The sequencing was used to provide an overview including a relative distribution

of microorganisms (on genus level) present in the UF retentates. The plot in Figure 15 shows the number of

observations (number of sequences which were identified during the Illumina sequencing) per sample. The

cut-off values in this case was set to 10,000 observations in order for a sample to be included for further

analysis. Five samples did not have sufficient number of sequences and were excluded for further analysis.

Figure 15. Shows the number of sequences per sample of each of the 38 UF concentrate samples collected during the UF process at Slagelse dairy.

0

5000

10000

15000

20000

25000

30000

35000

40000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38

Tota

l nu

mb

er o

f se

qu

ence

s

Sample number

Number of sequences for all the individual samples

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Figure 16 shows the average number of observed OUTs (Operational Taxonomic Units) for the start-samples

and the end-samles in each sample. The red line represents the average number of observed genera for the

samples collected at the end of the productions. The blue line represents the average number of observed

genera for the samples collected in the start of the productions.

This plot is often used to describe when the diversity of the samples is saturated based on the number of

sequences. In general, it seemed that the curves stabilized at 10,000 sequences. Therefore 10,000 sequences

might be a sufficient cut-off in order to properly describe the diversity of the samples.

Figure 16. Shows the development of the number of observed OTUs (Operational Taxonomic Units), including standard deviations in relation to the number of sequences for each UF milk concentrate sample. The plot illustrates how well the diversity of each sample is described based on 10,000 sequences. The blue curve represents the average of OTUs for the start-samples and the red curve represents the average of the OTUs for the end-samples obtained at Slagelse dairy.

Lastly, the plot also showed that the average diversity between the start-samples (blue line) and the end-

samples increased from approx. 40 OTUs up to approx. 50 OTUs. This might indicate that the microbial

diversity evolves during the concentration process. Moreover, the standard deviation indicated by the red

and blue vertical bars indicated a relatively large variation in the diversity of observed OTUs.

Figure 17 shows the relative (%) distribution of dominating bacteria in each of the included UF samples. It

was decided to include only the bacteria with a relative distribution >0.1% in order to visualize the result

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appropriately. The included bacteria are listed in Table 13 including their overall distribution in the samples,

the total count in the start-samples and in the end samples.

Figure 17. Relative distribution of bacteria in each of the 38 UF-samples collected at Slagelse dairy. A represents the samples collected in the start of the productions and B indicates the samples collected in the end of productions. Number 1-10 indicate the production number and 1-2 represent the replicate number. The samples are sorted according to production.

The samples were provided with an ID, based on whether it was collected in the start (A) or in the end (B) of

the production. 1-10 states the production number and 1-2 following the point represents the replicate

number.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

A2 A3 A4.1 A4.2 B4 A5.1 A5.2 B5.1 B5.2 A6.1 A6.2 B6 A7 B7.1 B7.2 A8.1 A8.2 B8 A9.1 A9.2 B9.1

Relative distribution of bacteria in each UF sample

Citrobacter spp. Microccus spp. Clostriales Ruminococcaceae

Streptococcus spp Microbacterium spp. Enterobacteriaceae Aeromonadaceae

Flavobacterium spp. Janthinobacterium spp. Acinetobacter spp. Pseudomonadaceae

Lactococcus spp. Anoxybaclllus spp. Pseudomonas spp. Thermus spp.

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Table 13. A list of the most abundant classes of bacteria in the 38 UF-samples collected at Slagelse dairy. The list includes the overall distribution of the bacteria in all of the 38 samples, the total count for all the start-samples and the total count for all the end-samples.

Groups of bacteria Overall distribution [%] Total counts in the

start-samples

Total counts in the

end-samples

Citrobacter spp. 0.2 118 492

Clostriales 0.2 274 201

Ruminococcaceae 0.3 494 219

Streptococcus spp 0.3 382 320

Microbacterium spp. 0.4 831 256

Enterobacteriaceae 0.5 383 931

Aeromonadaceae 0.7 801 1,066

Flavobacterium spp. 0.9 1,296 1,079

Janthinobacterium spp. 1.8 1,485 3,508

Acinetobacter spp. 2.6 1,240 5,680

Pseudomonadaceae 2.7 4,084 3,125

Lactococcus spp. 3.3 2,568 6,401

Anoxybaclllus spp. 9.9 17,254 9,460

Pseudomonas spp. 25.9 31,981 37,846

Thermus spp. 49.4 84,989 48,344

Based on the bar plot (Figure 17) and Table 13, it is evident that Thermus spp. (49.4%) was the most

dominating genus together with the Pseudomonas spp. (25.9%). Looking at the samples from production 9

(A9.1 & 2 and B9.1 & 2) Thermus spp. was dominating. In the end of production samples (A91.1 and 2),

however, it seemed that the abundance of Pseudomonas spp. increased. According to the samples from the

fifth production, however, Pseudomonas spp. dominated within the A5.1 and 2 as well as the B5.1 and 2.

Furthermore, looking at the total count for the start-samples and the end-samples, it seemed that Termus

spp. decreased from 84,989 counts down to 48,344 counts during the productions. For Pseudomonas spp. it

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seemed that they were able to grow slightly during the productions since it increased from 31,981 counts to

37,846 counts. Typically, 65-70% of the psychrotrophs isolated from raw milk are Pseudomonas spp. making

this group of bacteria the most predominant in cold stored raw milk. Even though psychrotrophs are capable

of producing heat stable proteolytic and lipolytic enzymes, they still have to grow to a number greater than

106 CFU/ml before altering the milk quality (Ledenbach & Marshall, 2009). Thermus spp. are thermophilic,

ubiquitous and specific species have been isolated in Icelandic hot springs where they were found to be

resistant to both acidic and alkaline pH (Kristjansson & Alfredsson, 1983). This means that they would

probably be able to colonize and grow in the heating equipment which was used to heat-treat the UF

concentrates. This may, therefore, explain the high relative distribution of Thermus spp. in practically all the

UF samples.

In order to inspect the similarities or dissimilarities between samples, alpha- and beta-diversities are often

used. In this case, the beta-diversity is used to consider the diversity between the samples as well as the

differences between the start- and end-samples. In order to inspect the weight beta-diversity, the data were

plotted in a Principal Coordinate Analysis plot (PCoA) (see Figure 18).

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It appears that both start and end samples are situated rather close to each other, indicating that the

microbial composition may not be different in the start samples compared to the end samples, overall.

Looking at samples within the same UF-production day, for instance production 4, there seemed to be a

rather large difference between the start samples (A4.1 &2) (marked by the black circle) and the end sample

(B4) (the red dot marked by the orange circle), which could indicate that bacterial composition changed

during the production. Comparing this trend to the bar plot in Figure 17, the A4.1 & 2 were clearly dominated

by Termus spp. in the start-samples, whereas, in the end-sample, Pseudomonas spp. was dominating. This

may explain the long distance between the samples in the PCoA plot of Figure 18. Looking at production 5,

however, it seemed that both the start samples (A5.1 & 2) and the end samples (B5.1 &2) located inside the

red circle were closely related, indicating that the microbial composition did not change during the UF

production. Again, comparing to the data from the bar-plot (Figure 17), Pseudomonas spp. were already

present in the start-samples and did only slightly increase during the production.

However, the bar-plot also seemed to illustrate that the microbial community varied greatly between the

days. Furthermore, this variation is probably caused by factors such as the hygienic standard, the health of

the cows and contamination from the environment on the individual farms which have been observed in

Figure 18. Shows a 3D PCoA plot, the relation between the UF samples collected at Slagelse dairy based on the weighted beta-diversity. The samples collected in the start of the productions are indicated by the blue dots and the samples collected after the productions are represented by the red dots. The closer the samples (dots) are, the more similar the samples are in terms of microbial composition.

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previous studies (Hayes et al., 2001; Hutchison et al., 2005; Rasolofo et al., 2010). However, when

interpreting the results from the Illumina sequencing it is important to have in mind that DNA from both

living and lysed cells are being amplified and sequenced. This means that the results provide an overview of

microbial community including dead cells. Based on the table showing the most abundant bacteria and

groups of bacteria (Table 13), these results are consistent with the findings of other studies which

investigated the microflora of cold stored raw milk (Hantsis-Zacharov & Halpern, 2007; Rasolofo et al., 2010).

Common to all the studies was that the bacterial community tends to be highly diversified, which was also

seen for the UF samples in the present study.

It was decided not to proceed with plating of the UF concentrates since it was thermized (65oC in 15 s.) after

concentration. However, for the first production, the beginning and after samples were plated on 1% milk

PCA and incubated tree days at 30oC. Table 14 contains the total average CFU/ml counted on the plates. For

the beginning-samples, the level of CFU/ml was 7.5*102 and 8.7*102, which was found to be a small and

insignificant increase.

Table 14. Shows the total CFU/ml counted at the start and at the end of the first UF-production at Slagelse dairy.

The 3D PCoA plot in Figure 19 shows the relations between all the UF samples based on the unweighted beta-

diversity. The position and distance between the samples are based on the presence/absence of bacteria in

the samples. Especially four samples (B1.1 & 2 and A1.1 & 2), marked by the black circle, are clearly separated

from the rest of the UF-samples.

Total CFU/ml for the first UF production: Start and End samples

Start End

Average (CFU/ml) Standard

deviation

Log

(CFU/ml)

Average (CFU/ml) Standard

deviation

Log (CFU/ml)

7.5*102a 4.5*102 2.9 8.7*102a 2.5*102 2.9

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These samples were based on the DNA, which was washed off the agar plates in order to identify the

microorganisms surviving the heat-treatment of the UF-concentrate. The green circle to the right in the plot

(Figure 19) marks the end-sample showing the total microflora based on DNA from both living and lysed cells.

Figure 19. 3D PCA plot based on unweighted beta-diversity between the samples in PC1 (39%), PC2 (11) and PC3 (9%), showing that four samples marked by the black circle based on the DNA extracted directly from the plates (A1.1 & 2 and B1.1 & 2) were clearly separated from the rest of the UF-samples from Slagelse dairy.

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Figure 20 shows the relative abundance of the bacteria in the UF sample A1, and bacteria, which were able

to grow after the heat treatment of the UF sample.

Figure 20. Shows the relative abundance of the bacteria which were able to grow after the thermization (65oC in 15s) of the UF concentrate. A represents the samples collected in the start of the productions and B indicates the samples collected in the end of productions. Number 1-10 indicates the production number and 1-2 represent the replicate number. For production 1, the UF-samples were plated on 1% milk PCA agar and “(Plate)” indicates that the DNA was extracted directly from the plates.

Obviously, Microbacterium spp. seems to be the dominating class of bacteria that was able to survive the

heat treatment and manage to grow afterwards. This is in agreement with the results of the study of Washam

et al., (1977), who found Microbacterium spp. to be thermoduric, which allow them to survive pasteurization

processes.

0%

20%

40%

60%

80%

100%

B1 A1.1 (plate) A1.2 (plate) B1.1 (plate) B1.2 (plate)

Relative distribution of bacteria able to grow after the thermization

Citrobacter spp. Microccus spp. Clostriales Ruminococcaceae

Streptococcus spp Microbacterium spp. Enterobacteriaceae Aeromonadaceae

Flavobacterium spp. Janthinobacterium spp. Acinetobacter spp. Pseudomonadaceae

Lactococcus spp. Anoxybaclllus spp. Pseudomonas spp. Thermus spp.

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4.2. Reverse-osmosis concentrates

4.2.1. Total CFU/ml measured at the start and at the end of the RO productions

The plot (Figure 21) shows the development in total CFU/ml during the three consecutive RO productions at

Arinco dairy (pasteurized skim milk) and the second and third production trial conducted at UCPH (raw skim

milk). The CFU/ml is shown on a semi-logarithmic scale based on start-samples collected approx. 30 min. into

the production and 20 min. before the end of the production.

The first three bars from the left (grey, yellow and light blue) corresponds to the three productions in three

consecutive days at Arinco dairy. It is important to note that the duration of the productions differs between

trials, e.g. day 1 (8h), day 2 (4.5h) and day 3 (8h).

Figure 21. Development in total CFU/ml during three RO productions at Arinco dairy with pasteurized milk (A.) and two RO production trials at UCPH with raw skimmed milk (B.). The data is based on samples which were collected approx. 30 min into the production and 20 min before the end of the production.

For production 1 and 3 at Arinco, only a slight, but significant increase in the total CFU/ml (0.2 log and 0.8 log

respectively) was observed. For production 2, an increase of 0.1 log was seen, but this was not significant

(see Figure 21.A and Table 15).

In Figure 21.B, the dark blue and orange bars indicate samples from the second and third trials at UCPH. The

results from the first production were excluded due to the fact that only a limited number of serial dilutions

were made, and it was not possible to determine the exact CFU/ml. Only a small insignificant increase (0.1

log) was observed, however, the start CFU/ml seems to be approx. 1.5 log higher compared to the start

CFU/ml at Arinco dairy. This was also seen for the third production, where the start CFU/ml was approx. 0.5

0,0

1,0

2,0

3,0

4,0

5,0

6,0

7,0

8,0

Start End

Log(

CFU

/ml)

A. Arinco dairy - total CFU/ml

Production 1 (8 h) Production 2 (4.5 h)

Production 3 (8 h)

0,0

1,0

2,0

3,0

4,0

5,0

6,0

7,0

8,0

Start End

Log(

CFU

/ml i

n m

ilk o

r co

nce

ntr

ate)

B. UCPH trials - total CFU/ml

2nd RO trial at UCPH (4.5 h)

3rd RO trial at UCPH (6 h)

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log higher than for the second production. Furthermore, a significant increase (1.1 log) was observed during

the production.

Table 15. Microbial growth data obtained during three RO productions at Arinco dairy with pasteurized milk and two RO production trials at UCPH with raw skimmed milk. The table includes counted average CFU/ml, log (average CFU/ml) and standard deviations for both start and end samples. Statistical differences were determined using t-tests (p-values<0.05).

Start

End

Average

(CFU/ml)

Standard

deviation

Log

(average

CFU/ml)

Average

(CFU/ml)

Standard

deviation

Log

(average

CFU/ml)

p-

values

p

<0.05

Arinco

dairy

Prod

1

1.86*104 1.36*103 4.3a

3.27E+04 0.1 4.5b 0.04

Prod

2

4.23*103 4.55*101 3.6a

5.36E+03 0.0 3.7a 0.06

Prod

3

1.30*104 4.09*102 4.1a

7.14E+04 0.0 4.9b 0.02

UCPH Trial

2

8.77*105 1.23*105 5.9a

1.10E+06 0.0 6.0a 0.2

Trial

3

4.68*106 2.27*105 6.7a

5.73E+07 0.1 7.8b 0.02

*Values in the same row not marked by the same capitals are significantly different using t-test p<0.05

The milk, which was used for the RO productions at UCPH, was collected at Slagelse dairy, where it was

skimmed at 55oC and filled into 10L sterile jugs. Afterwards, it was stored at 4oC until it was collected and

transported into UCPH to be stored overnight at 4oC. The fact that the raw milk was separated at 55oC and

stored in 10L containers at 4oC, combined with approx. 1.5h of transportation into UCPH probably explains

the elevated CFU/ml in both start samples. Furthermore, when the milk for the third production was

collected, it was noted that the milk was still warm, which might explain the very high start CFU/ml for the

third production. Another factor explaining the differences between the samples from Arinco dairy and the

samples from UCPH could be that dairy low-pasteurized milk was used at Arinco. This will generally lead to a

lower CFU/ml in the start samples compared to the raw skim milk from Slagelse dairy.

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At Arinco dairy, samples of the final concentrate skim milk were collected at the start and in the end of the

production. This means that the dry matter of the concentrate was the same DM (25%) in the start-sample

and in the end-sample. Thus, the results should indicate whether microorganisms were able to grow in the

application during the process. A significant increase of microorganisms was seen for both the first and third

production indicating that the microorganisms were able to grow slightly during the production.

However, for production trials at UCPH, the filtration process was carried out as a batch process meaning

that a constant volume of milk was concentrated gradually. Therefore, it should be expected that the sample

collected in the beginning of the trial would show the microbial load in the less concentrated milk (approx.

10% DM) whereas the end of production samples would represent the microbial load in the 30% DM.

Therefore, it would be expected that the CFU/ml should increase according to the concentration of the

concentrate, approx. 3 times. If that is the case, the CFU/ml during the second production trial declined

during the batch filtration process, since the CFU/ml only increased from 8.77*105 to 1.10*106 CFU/ml,

approx. 0.25 times. This trend was also seen as part of the unpublished results by Ida Sørensen (2017). Here

it was suggested that processing conditions caused the microorganisms to lyse or cluster together (Sørensen,

2017). In contrast to this, Partrício et al. (2014) found that cultures which were exposed to shear stress for

extended periods of time resulted in increased numbers of clusters but with fewer individual bacteria. This

suggests that the CFU/ml would increase because of the high shear stress during the RO concentration

process.

However, for the second RO production trial, the CFU/ml increased from 4.68*106 to 5.73*107CFU/ml,

approx. 11 times, which was even more than the concentration factor. This is most likely due to the electrical

power supply problems which caused an approx. 1.5hs down-time during the production. Thus, the unit was

unable to cool the milk in the system and hence promoted the growth of microorganisms.

In industrial RO application, the system is more or less completely closed in order to limit the risk of

contamination from the production environment. The RO pilot unit, however, did have an open balance tank

which allowed microorganisms colonizing on the retentate/permeates hoses or from the air entering the

unit. The open balance-tank and the fact that the raw milk was manually poured into the tank, may also have

allowed for more air to enter the system. This may also have contributed to the growth of the aerobic

microflora in the milk.

Furthermore, the small pilot unit may also hold more dead-end points compared to an industrial application

where the bacteria could colonize and form biofilm.

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4.2.2. Illumina results

The Illumina samples prepared from the RO concentrates collected at Arinco dairy, were sent for sequencing

along with the UF samples. Unfortunately, the RO Illumina samples were not sequenced. Therefore, these

samples were prepared and sent for sequencing a second time. However, the results were not received

before the submission of this report.

4.2.3. Rep-PCR and cluster analysis

In order to obtain an initial overview of the diversity among the different bacteria isolated from the RO

samples, rep-PCR was performed. During the rep-PCR DNA fragments of different sizes were generated.

These fragments were then separated during the gel-electrophoresis, providing each isolate with a band

pattern. An example of a typical rep-PCR gel is shown in Figure 22. The difference between Illumina

sequencing and rep-PCR is that rep-PCR provides a band-pattern which allows one to distinguish between

different groups of bacteria. Illumina sequencing, however, provides both identification and a relative

distribution of the microorganisms.

The different isolates were clustered according to the individual band patterns. This means that isolates that

hold the same band patterns are placed in the same groups. Therefore, instead of preparing all the isolates

for 16S rRNA gene sequencing, only a representative number of isolates from each cluster are prepared. The

number is usually defined by the square root of the total number of isolates in the same cluster (e.g. with 15

isolates in the same cluster, √15 = 4 isolates are prepared for sequencing)

A total of 44 bacteria were isolated from RO concentrate made from pasteurized skim milk collected at Arinco

dairy and 30 bacteria from raw RO concentrate collected in the first RO production trial and second RO

production trial, respectively. All bacteria/colonies were selected from 1% milk PCA (incubated at 30oC in

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three days). Two cluster analyses were performed; one for the isolates from Arinco dairy (pasteurized skim

milk) and one for the isolates from production trials at UCPH (raw skim milk).

Figure 22: An example of a typical electrophoresis gel where the rep-PCR fragments have been separated.

Figure 23 shows an example of a cluster-analysis. This particular cluster-analysis was perfromed based on the

44 isolated from Arinco dairy.

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Figure 23. Cluster-analysis performed on all 44 isolates from RO concentrates obtained from Arinco dairy. The results from the BLAST search are listed to the left.

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Some areas of the gels appeared very dark. This made it difficult to clearly locate some of the bands in those

areas. This means that some of the isolates will generate their own unique clusters even though they might

have the same band pattern as some of the other isolates. This reduced the ability to identify either groups

or distinguish some of the isolates from each other (see Figure 22). This may also explain the random location

of some of the isolates in the cluster analysis even though they turned out to be identified as the same species

as some of the other isolates, based on the results from the 16S rRNA gene sequencing. The cluster-analysis

of the isolates from the two RO productions of UCPH can be found in Appendix, section 4.1 to 4.3.

4.2.4. 16S rRNA gene sequencing results

4.2.4.1. Arinco dairy

Based on the picture of the gels, groups of band patterns were identified and as a minimum, the square root

of the number of isolates in each of the groups were selected for 16S rRNA gene sequencing. The following

three tables (Table 16Table 17Table 18) show the results from the BLAST search.

Table 16. 16S rRNA gene sequencing results based on isolates from Arinco dairy

Isolate

no.

Closest

phylogenetic

affiliation in

Genbank

Genbank

Accesion

no.

Seque

nce

length

(bp)

Max

Score

Query

Cover

%

E-

value

Identit

y %

Gram-

test

(+/-)

Catalase-

test

(+/-)

Colony pigment

1 Microbacterium

lacticum

NR_02616

0 1100 1977 100 0.0 99.1 + + Grey

2 Microbacterium

lacticum

NR_02616

0 1050 1812 100 0.0 97.9 + + Grey

3 Microbacterium

lacticum

NR_02616

0 1200 2061 99 0.0 97.7 + + Yellow

5 Microbacterium

lacticum

NR_02616

0 1350 2148 98 0.0 95.9 + + Grey

112 Microbacterium

lacticum

NR_02616

0 1100 1945 100 0.0 98.5 + + Grey

114 Microbacterium

lacticum

NR_02616

0 1200 2084 100 0.0 97.9 + + Grey

115 Microbacterium

lacticum

NR_02616

0 1250 2128 98 0.0 98.0 + + Grey

21 Microbacterium

lacticum

NR_02616

0 1200 2065 100 0.0 97.7 + + Grey

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Table 16 gives an overview of the results from the BLAST search for the 16 isolates from Arinco dairy, which

were selected for 16S rRNA gene sequencing. The table includes isolate number, closest relative in the

Genbank database, the Genbank accession number, the length of the sequence BLAST’ed and the identity

percentages. Furthermore, the table includes the results from the Gram-test and catalase-test. The “+”

(positive) sign means that the isolate was Gram-positive or catalase-positive.

For these 16 isolates, the 27F and 800R primers were used by Macrogen to process the 16S rRNA gene

sequences. However, the 800R primer gave low quality reads and thus it was not possible to align the forward

and reverse primer sequences. The results are, therefore, based on a single sequence from the 27F primer

and not the consensus sequence, which is generated when the forward and reverse primer sequences are

aligned in CLC Workbench. This means that there is a potential risk that the identity of the isolate on species

level may be different.

Therefore, 13 of the 16 isolates came up with Gram-positive and catalase-positive Microbacterium lacticum

as the closets relative in the Genbank database (12 of these with similarities ≥97%). Furthermore, all these

isolates were determined to be both Gram-positive and catalase-positive.

When the samples were plated on 1% milk PCA plates, two types of colonies tended to interfere with other

colonies by either growing on large parts of the plates or completely overgrowing the whole plate. Therefore,

isolate -21 and -22 were isolated from two plates where one colony was covering the entire plate. Isolate -

22 Microbacterium

lacticum

NR_02616

0 1200 2073 99 0.0 97.9 + + Grey

25 Primer sequences were too bad quality + + Yellow

26 Microbacterium

lacticum

NR_02616

0 1200 2047 100 0.0 97.4 + + Grey

27 Microbacterium

lacticum

NR_02616

0 1200 2134 100 0.0 98.8 + + Yellow

28 Microbacterium

lacticum

NR_02616

0 1200 2115 99 0.0 98.6 + + Yellow

29 Microbacterium

lacticum

NR_02616

0 1100 1965 100 0.0 98.9 + + Grey

-21 Paracoccus

sanguinis

NR_13588

3 1050 1917 100 0.0 99.6 - + Grey/white

-22 Bacillus

licheniformis

NR_11899

6 1100 1341 90 0.0 90.4

+

+

Yellow

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21 is identified as Gram-negative and catalase-positive Paracoccus sanguinis with a similarity of 99.6%. Since

isolate -22 has a similarity of 90.4% with B. linchenformis, it would be appropriate to state that the isolate is

closely related to a Gram-positive and catalase-positive Bacillus spp.. In order to limit the growth of these

interfering bacteria, additional agar was added to the 1% milk PCA (4% agar in total), showed good effect.

Hence, this medium was used for the following plating.

Since, it was pasteurized skim milk, which was used for the RO filtration at Arinco dairy, the results indicate

that the bacteria survived the pasteurization as it was seen for Microbacterium spp. in the heat-treated UF

samples. However, the bacteria may also have been introduced in the milk as a result of post-contamination.

Paracoccus spp. are commonly isolated from environmental sources, such as mud, soil and ground water,

which may explain why P. sanguinis was found in the milk. Although its growth optimum temperature is 28oC,

growth of this bacteria has been observed between 4-55oC. Paracoccus spp have also previously been found

to survive pasteurization processes (Myer et al., 2016).

Bacillus spp. are also well-known to survive pasteurization processes and especially the thermoduric and

thermophillic Bacillus spp., such as B. cereus and B. subtilis are regularly associated with spoilage of milk

powders (Hutchison et al., 2005; Murphy et al., 1999)

4.2.4.2. UCPH

The following Table 17Table 18 contains the results from 16S rRNA gene sequencing and subsequent BLAST

search for 43 isolates from the first and second RO production carried out at UCPH with raw skim milk from

Slagelse dairy.

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Table 17. 16S rRNA gene sequencing results based on isolates from 1st RO production at UCPH

Isolate

number

Closest

phylogenetic

affiliation in

Genbank

Genbank

Accesion

no.

Sequence

length

(bp)

Max

Score

Query

Cover

%

E-

value

Identity

(%)

Gram-

test (+/-)

Catalase-

test (+/-)

1 Macrococcus

caseolyticus

NR_119262

848 1402 98 0.0 96.8 + +

2 Escherichia

fergusonii NR_074902 884 1363 99 0.0 95.1 - +

7 Macrococcus

caseolyticus

NR_119262

880

1498 100 0.0 97.4 + +

11 Macrococcus

caseolyticus

NR_119262

879

1580 99 0.0 99.1 + +

14 Escherichia

fergusonii

NR_074902 1130

1916 99 0.0 97.4 - +

15 Escherichia

fergusonii

NR_074902 879

1493 99 0.0 97.5 - +

17 Hafnia paralvei NR_116898

1031 1672 99 0.0 95.8 - +

19 Shigella sonnei* NR_104826 950 1688 99 0.0 98.8 - +

20 Escherichia

fergusonii

NR_074902 847

1515 99 0.0 98.9 - +

23 Macrococcus

caseolyticus

NR_119262 873

1572 99 0.0 99.3 + +

25 Shigella flexneri NR_026331 911

1463 98 0.0 96.1 - +

26 Escherichia

fergusonii NR_027549 1135 1829 99 0.0

95.8

- +

28 Shigella

dysenteriae *

NR_026332

850

1537 99 0.0 99.5 - +

*: Gene sequences could not be aligned. Therefore, only the sequence from 27F primer was BLAST´ed

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Table 18. 16S rRNA gene sequencing results based on isolates from 2nd RO production at UCPH

Isolate

number

Closest

phylogenetic

affiliation in

Genbank

Genbank

Accesion

no.

Sequence

length

(bp)

Max

Score

Query

Cover

%

E-

value

Identity

(%)

Gram-

test

(+/-)

Catalase-

test (+/-)

1 Macrococcus

caseolyticus

NR_119262

815 1500 100 0.0 99.9

+ +

2 Lactococcus

lactis

NR_113960

1224 2210 99 0.0 99.3

+ -

3 Macrococcus

caseolyticus

NR_119262

1206 2170 99 0.0 99.3

+ +

4 Macrococcus

caseolyticus

NR_119262

1143 2076 99 0.0 99.5

+ +

5 Lactococcus

lactis

NR_113960

1198 2189 99 0.0 99.7

+ -

6 Staphylococcus

aureus

NR_037007

1186 2134 99 0.0 99.2

+ +

7 Lactococcus

lactis

NR_113960

1225 2209 99 0.0 99.2

+ -

8 Macrococcus

caseolyticus

NR_119262

1204

2189 99 0.0 99.5 + +

9 Lactococcus

lactis

NR_113960

1202

2207 99 0.0 99.8 + -

10 Leuconostoc

lactis

NR_113255

1128

1725 99 0.0 93.8 + -

11 Macrococcus

caseolyticus

NR_119262

1140 2087 99 0.0 99.7

+ +

12 Enterococcus

faecalis

NR_113901

1180 2145 99 0.0 99.5

+ -

13 Macrococcus

caseolyticus

NR_119262

1174 2128 100 0.0 99.4

+ +

14 Enterococcus

faecalis

NR_113901

1130 2080 99 0.0 99.9

+ -

15 Enterococcus

faecalis

NR_113901

1201 2178 99 0.0 99.4

+ -

16 Escherichia

fergusonii

NR_074902

1158 2056 98 0.0 99

- +

17 Macrococcus

caseolyticus

NR_119262

1223 2200 99 0.0 99.2

+ +

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Comparing the results obtained with the isolates from Arinco, the distribution of Gram-negative bacteria,

such as Escherichia fergusonii, Shigella spp. (S. dysenteriae, S. flexneri and S. sonnei) and Hafnia spp.

increased which was expected since the milk had not been pasteurized. This may also explain the wider range

of different Gram-positive bacteria, which were also identified such as Macrococcus caseolyticus, Lactococcus

lactis, Leuconostoc lactis, Enterococcus faecalis and Staphylococcus aureus. In general, the microbial

population seems to comply with what have been isolated in other studies investigating the raw milk

microbial composition (Oliveira et al., 2015; Rasolofo et al., 2010). However, it is interesting that none of the

isolates were identified as Pseudomonas spp. Several studies have isolated Pseudomonas spp. from raw bulk

milk and combined the Illumina sequencing results revealed that Pseudomonas spp. were the second most

18 Lactococcus

lactis

NR_113960

1232 2246 99 0.0 99.7

+ -

19 Macrococcus

caseolyticus

NR_119262

1174 2126 99 0.0 99.4

+ +

20 Macrococcus

caseolyticus

NR_119262

1213 2196 99 0.0 99.3

+ +

21 Macrococcus

caseolyticus

NR_119262

857 1578 100 0.0 99.9

+ +

22 Lactococcus

lactis

NR_113960

1165 2119 99 0.0 99.5

+ -

23 Leuconostoc

lactis

NR_113255

1145 2098 99 0.0 99.7

+ -

24 Leuconostoc

lactis

NR_113255

1196 2150 99 0.0 99.2

+ -

25 Enterococcus

faecalis

NR_113901

1212 2178 99 0.0 99.3

+ -

26 Lactococcus

lactis

NR_113960

1225 2196 99 0.0 99

+ -

27 Leuconostoc

lactis

NR_113255

1250 2276 99 0.0 99.5

+ -

28 Lactococcus

lactis

NR_113960

1191 2182 99 0.0 99.7

+ -

29 Leuconostoc

lactis

NR_113255

1149 2095 99 0.0 99.6

+ -

30 Macrococcus

caseolyticus

NR_119262

849

1563 100 0.0 99.6 + +

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abundant genus in the UF samples (Desmasures et al., 1997; Holm et al., 2004). Therefore, one would expect

some levels of Pseudomonas spp. in the raw milk from Slagelse dairy. It is important to note that these results

from the 16S rRNA gene sequencing and subsequent BLAST search provide a good indicator of the microbial

community in the RO samples (Rasolofo et al., 2010). However, as it is with culture dependent methods, it is

only the bacteria which can grow on the 1% milk PCA (4% agar) medium at 30oC that are selected for the 16S

rRNA gene sequencing (Mayo et al., 2014). Therefore, it is a possibility that some bacteria do not grow under

these specific conditions and therefore cannot be isolated and identified using the 16S rRNA gene sequencing

even though they might be present in the RO retentates.

4.3. RO concentrate manufacture process chart

Figure 24 shows the process charts based on the development in dry matter (DM) [%] and feed pressure

monitoring during second and third RO production trials. Table 19 includes the production times [h], the

desired dry matter, the actual DM in the collected retentate samples, the feed pressure and the

concentration factor (only for the second trail). Calculation of the dry matter including the data from the DM

determination can be found in Appendix, section 2.

For the second production trial, the dry matter goes from 9.6% for the unconcentrated raw milk up to 29.4%

for the last sample. The feed pressure applied during the process goes from 20 bars, 27 bars, 31 bars and to

32 bars. Furthermore, the concentration factor was initially 1.8 but was decreased gradually down to 1.4 and

eventually 1.2 due to more and more water being removed.

0

5

10

15

20

25

30

35

0

5

10

15

20

25

30

35

0 2 4 6

Feed

Pre

ssu

re [

bar

]

Dry

mat

er c

on

ten

t [%

]

Time [h]

2nd production trial

Dry matter content Feed pressure

0

5

10

15

20

25

30

35

40

0

5

10

15

20

25

30

35

0 2 4 6 8

Feed

pre

ssu

re [

bar

s]

Dry

mat

er c

on

ten

t [%

]

Time [h]

3rd production trial

Dry matter content Feed pressure

Figure 24. Shows the development of specific process parameters during second and third RO production at UCPH

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For the third production trial, the dry matter for the raw milk was also 9% and the collected retentate samples

contained 14.1%, 22.2%, 24.2% and 29.3%. The feed pressure was initially at 20 bars and was gradually

increased to 30 bars, 34 bars, 34 bars and finally 36 bars. Unfortunately, the concentration factor was not

registered during this production.

Generally, for both productions, it was observed that as the dry matter content increased so did the feed

pressure. This complies well with the fact that it requires more pressure to maintain the flux of water through

the membrane when the dry matter content increases. Looking at Figure 24, the gap between the third and

fourth samples is due to the down-time caused by the electrical power supply problems and explains the

long time between the two samples.

Table 19. Shows the time, desired DM, actual DM, pressure and concentration factor which were monitored during

the second and third RO production at UCPH.

Time [h] Targeted

DM [%]

Actual DM

[%]

Pressure [bars] Concentration-

factor

2nd trial 0

9.6 0

1.5 15 14.3 20 1.8

2.5 20 21.9 27 1.4

3.5 25 25.3 31 1.2

4.5 30 29.4 32 1.2

3rd trial 0.0

9.6 0

1.5 15 14.1 20

2.2 20 22.2 30

5.2 25 24.2 34

6.2 30 29.3 36

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4.4. Heat-inactivation of M. lacticum in raw RO skim milk retentates

In order to understand the thermal stability of bacteria in RO concentrates made from skim milk, isolates of

M. lacticum were inoculated in RO concentrates with different dry matter content. These concentrates were

subsequently heat treated at temperatures between 57-72oC up to 180s. Thereby it is possible to examine

whether the heat resistance of the bacteria is affected by the different DM concentrations.

M. lacticum has frequently been reported to be part of the psychrotrophic microflora of raw milk, however,

growth has also been observed between 20-40oC (Hantsis-Zacharov & Halpern, 2007; Laffineur et al., 2003).

Furthermore, the genus Microbacterium has also shown both lipolytic and proteolytic activity (Hantsis-

Zacharov & Halpern, 2007). Based on this, combined with the ability of certain species of Microbacterium,

including M. lacticum to survive pasteurization processes, it was suggested that Microbacterium spp. could

serve as an important indicator for quality of raw milk (Hantsis-Zacharov & Halpern, 2007). Furthermore, in

this experiment, the bacteria were isolated from industrial RO membrane filtration plant. This means that

the bacteria have adapted to the complex process conditions and environment. It is likely that this would

also increase their resistance towards the heat-treatments, compared to cultured laboratory strains, which

have been grown under ideal conditions and thus are not as resistant. Thereby, the results were expected to

provide a more “real-life” indication on the effect of the heat treatments (Palková, 2004).

Additionally, the 16S rRNA gene sequencing results, based on the isolates from RO samples obtained at

Arinco dairy, showed that M. lacticum was very abundant in the RO concentrate. Therefore, it was decided

to select M. lacticum for the heat inactivation study. Since all of the isolates of M. lacticum, had either a

grey/white or yellow/orange colony pigment, two different isolates of M. lacticum (103: yellow and 112:

grey) with different pigments were chosen.

The inactivation study was conducted using the RO skim milk concentrates produced in third RO production

trial UCPH. Since, the thermal inactivation experiments were not conducted directly after the third RO

production trial, samples of different concentrates were frozen at -20oC. Moreover, it was assumed that the

freezing process would reduce microbial load in the concentrates. Furthermore, it was assumed that by

inoculating the ON-culture of M. lacticum, it would overrule the existing microflora in the raw concentrates.

Hence, it was decided to use the raw RO concentrates in the thermal inactivation experiments.

It was also decided not to add additional agar to the 1% milk PCA medium, fearing that it would have an

influence on the results. However, this resulted in growth of interfering colonies, which tended to take over

large parts of the plates (see Figure 25). This problem has also previously been reported by Dega et al., (1972)

when the growth of S. thyphimurium in skim milk concentrates was investigated. Therefore, it was decided

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to qualitatively register if there were growth of M. lacticum (isolate 103 and 112) at the different dilutions,

based on the pigment of the colonies, rather than counting the individual colonies. However, this would

naturally bias the results, as it can be rather difficult to distinguish between microorganisms solely based on

the colony pigments. Therefore, the results of the thermal inactivation experiments should probably be

considered as a preliminary study investigating the potential influence of the DM content on the heat

resistance of M. lacticum rather than an examination of the precise inactivation kinetics of M. lacticum.

4.4.1. Estimated heat-up and cool-down times tubes during the thermal inactivation

experiments

The stainless-steel tubes were designed based on a thin wall (2mm) stainless-steel tube with an external

diameter on 6mm and internal diameter on 4mm. Therefore, it was assumed that the heat-up and cooled-

down times would be rather short and almost negligible. However, in order to validate this assumption,

theoretical heating and cooling times were calculated (see Figure 26).

Figure 25. Shows an example when interfering microorganisms were growing on the 1% milk PCA (without additional agar)

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Figure 26.Shows the calculated heat-up and cool-down profiles for the tubes at 72 oC (blue), 67 oC (grey), 62 oC (yellow) and 57 oC (orange).

The convective heat transfer coefficient, h, was estimated to 500 W/m2oC since the water in the water-bath

was slightly agitated. The Biot number was calculated to be 1.6 using equation 6 listed in section 2.4.1.

Unfortunately, this means that the assumption based on the lump capacity analysis Nbiot < 0.1 was not valid.

However, it was decided to consider the internal resistance negligible to heat transfer, as it was assumed

that the temperature inside the tube was nearly uniform along the tube. Furthermore, the exact convective

heat transfer coefficient and thermal conductivity were only estimates and therefore it was decided not to

perform a more complicated calculation.

The heating and cooling times were calculated using equation 7 in section 2.4.1 and examples of the

calculations can be found in Appendix, section 6.

The initial heat-up times before the tubes reach 57oC, 62oC, 67oC and 72oC were approximately 20s and the

cooling-time down to below 10oC was nearly 10s and cooling all the way down to 4oC took approx. 30s in

total.

0

10

20

30

40

50

60

70

80

0 10 20 30 40 50 60 70 80 90 100 110

Tem

per

atu

re [

˚C]

Time [s]

Calculated heat-up and cool-down profiles

72˚C 67˚C 62˚C 57˚C

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Even though some estimates were used in the calculations, it still seemed that the heat-up time and cool-

down times are relatively short. However, the times should still be taken into account when interpreting

the results.

4.4.2. Thermal inactivation experiments

The results from the heat-inactivation experiments are shown in plot A1 and A2 for 57oC, B1 and B2 for 62oC,

C1 and C2 for 67oC and D1 and D2 for 72oC are shown in Figure 27 and Figure 28. For each heating

temperature (A, B, C and D), two separate heating experiments were conducted (1 & 2). Furthermore, for

each experiment, duplicates were made of each concentrate at each of the heating times. This means that

for one experiment with five samples with different dry matter, heated for five different times give a total of

50 measurements per experiment.

Figure 27 shows the data obtained from the experiments using 57oC (A) and 62oC (B) as heating temperatures.

In the first experiment (A1) at 57oC, it was not possible to determine the effect of the inactivation in 15% DM

sample, as well as the CFU/ml at “0s” for the 25% DM sample due to interfering organisms. The same issue

turned out for the second experiment A2, where it was only possible to determine the effect of heat

treatment for the 25% DM sample. For both experiments, however, it seemed that heat-treatment at 57oC

have a slight promoting effect on the growth, rather than an inactivating effect.

In the first experiment, B1, at 62oC, the initial CFU/ml varied between log 3.5 to log 4.5. The highest rate of

inhibition of M. lacticum appeared in the raw unconcentrated milk sample followed by the 20% DM sample.

The inactivation in 15% DM and 25% DM seemed to follow the same pattern. The slowest rate of inactivation

was seen for the 30% DM sample. This experiment seemed to show a slight tendency that the effect of heat-

treatment declined as the DM content increased, which complies with what has previously been suggested

(Kornacki & Marth, 1993). However, when the experiment was repeated in experiment A2, the same trend

was not seen.

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Figure 27. Shows the inactivation of M. lacticum (isolate 103 & 112) from each of the two experiments (1 & 2) carried out at 57oC (A1 & A2) and 62oC (B1 & B2). In each plot, five different colored lines represent the different retentates with varying DM; Dark blue; raw milk (9.6% DM), Orange; 15% DM, grey: 20% DM, yellow: 25% DM and light blue: 30% DM. Each retentate heated for 0, 30, 60, 120 and 180s.

0,00

1,00

2,00

3,00

4,00

5,00

6,00

7,00

8,00

0 30 60 90 120 150 180 210

log

(CFU

/ml)

Heating time [s]

A1 57oC - 1st experiment

0

1

2

3

4

5

6

7

8

0 30 60 90 120 150 180 210

log

(CFU

/ml)

Heating time [s]

A2 57oC - 2nd experiment

0

1

2

3

4

5

6

7

8

0 30 60 90 120 150 180 210

log

(CFU

/ml)

Heating time [s]

B1 62oC - 1st experiment

0

1

2

3

4

5

6

7

8

0 30 60 90 120 150 180 210

log(

CFU

/ml)

Heating time [s]

B2 62oC 2nd experiment

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The same inactivation pattern which was observed at 62oC also seemed to appear in the first experiment at

67oC (see Figure 28, C1). The highest rate of inactivation was seen in the unconcentrated raw milk sample,

followed by the 15% DM sample. Initially, the rate of inactivation was higher for the 30% DM compared to

both 20% and 25 % DM. However, the CFU/ml level stabilized at log 1 for the 30% DM sample, whereas for

both the 20% and 25% DM samples, M. lacticum was completely inactivated after 180s. In the second

experiment C2, it was only in the 15% and 20% DM samples that M. lacticum was inactivated and only very

little in the raw milk.

For both experiments at 72oC, M. lacticum seemed to be completely inactivated in all samples already after

30s.

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0

1

2

3

4

5

6

7

8

0 30 60 90 120 150 180 210

Log

(CFU

/ml)

Heating time [s]

C1 67oC - 1st experiment

0

1

2

3

4

5

6

7

8

0 30 60 90 120 150 180 210

Log

(CFU

/ml)

Heating time [s]

C2 67oC - 2nd experiment

0

1

2

3

4

5

6

7

8

0 30 60 90 120 150 180 210

Log

(CFU

/ml)

Heating time [s]

D1 72oC - 1st experiment

0

1

2

3

4

5

6

7

8

0 30 60 90 120 150 180 210

Log

(CFU

/ml)

Heating time [s]

D2 72oC - 2nd experiment

Figure 28. Shows the inactivation of M. lacticum (isolate 103 & 112) from each of the two experiments (1 & 2) carried out at 57oC (C1 & C2) and 62oC (D1 & D2). In each plot, five different colored lines represent the different retentates with varying DM; Dark blue; raw milk (9.6% DM), orange; 15% DM, grey: 20% DM, yellow: 25% DM and light blue: 30% DM. Each retentate heated for 0, 30, 60, 120 and 180s.

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In order to better evaluate the magnitude of the effects of the heat treatments, D- and z-values were

determined. This was done based on the data shown in B1 and C1 in Figure 29 and Figure 30, respectively.

The decimal reduction times, D-values, were calculated based on the negative inverse slope (k) of the dotted

lines, which were generated for each of the retentate samples (see plot B1 and C2 in Figure 29 and Figure

30). The z-values were calculated based on the D-values obtained from two plots (B1 and C1). The k, D-values

and z-values are listed in Table 20.

Figure 29. Shows the results from B1 at 62oC with tendency-lines added. The slope of these lines defines the k for each sample. Dark blue; raw milk (9.6% DM), orange; 15% DM, grey: 20% DM, yellow: 25% DM and light blue: 30% DM. Each retentate heated for 0, 30, 60, 120 and 180s

Raw milk: y = -0,03x + 3,7

15 DM: y = -0,0187x + 4,5

20 DM: y = -0,0348x + 4,7

25 DM: y = -0,0088x + 4,4

30 DM: y = -0,0069x + 4,1

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

4,5

5,0

0 30 60 90 120 150 180 210

log

(CFU

/ml)

Heating time [s]

B1 62oC with tendency-lines for all samples

Raw milk 15DM 20DM

25DM 30DM Lineær (Raw milk)

Lineær (15DM) Lineær (20DM) Lineær (25DM)

Lineær (30DM)

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Figure 30. Shows the results from C1 at 67oC with tendency-lines added. The slope of these lines defines the k for each sample. Dark blue; raw milk (9.6% DM), orange; 15% DM, grey: 20% DM, yellow: 25% DM and light blue: 30% DM. Each retentate heated for 0, 30, 60, 120 and 180s

To calculate the D-values, it was assumed that a first order kinetic and the heat-inactivation curves should be

straight lines when plotted on semi-logarithmic scale as illustrated in Singh & Heldman, (2013). This was not

the case for all of the samples in these trials. At 62oC (plot B1) the inactivation curve for all the samples

seemed to have a fairly linear declining pattern, however, at 67oC (trial C1), specially for retentates at 20%,

25% and 30% DM) the curve has a characteristic “tail”. These tails may have been the result of an interfering

microorganisms which could have led to false registration of growth of M. lacticum. However, it is also a

possibility that the two isolates of M. lacticum (103 and 112) did not share the same inactivation pattern and

thereby were inactivated to different levels. The consequence of the “tail” is that it reduces the slope (k) and

eventually increases the final D-value, but overestimates the inactivation for longer times.

In Table 20, the k constants, D-values and z-values are listed for each of the samples at both 62oC and 67oC.

Examples of the calculations used for determination of D- and z-values are shown in Appendix, section 0. At

62oC, the D-value was 1.3 min for the raw unconcentrated milk, 1.9 min for 15% DM, 1.1 for 20% DM, 4.8

min for 25% DM and 5.6 min for 30% DM. This shows that the decimal reduction time for 30% DM compared

Raw milk: y = -0,133x + 4

15 DM: y = -0,067x + 3,7

20 DM: y = -0,017x + 3,5

25 DM: y = -0,025x + 4,1

30 DM: y = -0,017x + 3,5

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

4,5

5,0

0 30 60 90 120 150 180 210

Log

(CFU

/ml)

Heating time [s]

C1 67oC with tendency-lines for all samples

Raw milk 15DM 20DM

25DM 30DM Lineær (Raw milk)

Lineær (15DM) Lineær (20DM) Lineær (25DM)

Lineær (30DM)

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to the raw unconcentrated milk is approx. 4 times longer. Furthermore, the D-value for 20% DM was 0.8 min

shorter than the 15% DM and 0.2 min shorter than for the raw milk.

Table 20. Show the k-values, D-values for M. lacticum in raw non-concentrated milk and RO milk retentates with DM concentration ranging from 15 to 30% at 62oC and 67oC. Based on the D-values, z-values were calculated for each retentate sample.

Retentate sample k (62 oC) k (67 oC) D62oC D67oC z-values [oC]

Raw milk 0.03 0.133 1.3 min 17.3s 7.7

15 DM 0.02 0.067 1.9 min 34.4s 9.5

20 DM 0.03 0.017 1.1 min 2.3 min N/A*

25 DM 0.008 0.025 4.8 min 1.5 min 10.1

30 DM 0.0069 0.017 5.6 min 2.3 min 12.8

*N/A: Not applicable

At 67oC, the D-values for raw unconcentrated milk is 17.3s, 34.4s for 15% DM, 2.3 min for 20% DM, 1.5 min

for 25% DM and 2.3 min for 30% DM., The measured D-value for the 20% DM is twice as long at 67oC

compared to 62oC and this is probably due to experimental error and therefore the z-value was not

calculated. However, for the rest of the samples, as expected the D-values decrease with increase of

temperature from 65oC to 67oC. The z-value is 7.7oC for the raw unconcentrated milk, 9.5oC for 15% DM,

10.1oC for 25% DM and 12.8oC for 30% DM, showing that the composition of the concentrate influences the

thermal stability of the bacteria.

Relatively few studies have investigated the thermal resistance of M. lacticum in terms of determination of

decimal reduction times. M. lacticum has also been found to be one of the most heat-resistant bacteria in

pasteurized whole egg with negligible loss of viability after 60 min at 65oC (Payn et al., 1979). However, based

on these results, it seems that the samples with increased dry matter content require longer heating times

in order to eliminate 90% of inoculated M. lacticum. Furthermore, it makes sense that the D-values decrease

when the temperature was increased from 62oC to 67oC. The increased heat resistance of bacteria in milk

concentrates has also been seen for several other bacteria, such as E. coli (0104:H7), S. Alachua , S.

thyphimurium as well as M. freudenreichii and S. senftenberg when their heat inactivation kinetics were

investigated in milk retentates (Dega et al., 1972; Dega & Goepfert, 1972; Kornacki & Marth, 1993). The D-

values for E. coli in 10% and 42% reconstituted skim milk samples at 57oC, 56.8oC and 55.7oC were determined

to be 1.8, 2.4 2.9 and 2.3, 3.0, 4.3 respectively. For S. typhimurium (at the same dry matter contents and

temperature) the D-values were determined to be 1.4, 2.0, 3.2 min and 2.9, 4.1, 5.4 min. However, it should

be noted that it is rather difficult to compared D-value between studies, since even small variations in heating

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methods, composition of the milk concentrate and bacterial cultures can affect the final decimal reduction

times and z-values.

5. Project conclusion

The aim of this project has been to identify, select and study the growth and thermal inactivation of selected

microorganisms normally found in commercial RO concentrates.

Determination of total CFU/ml from three commercial RO productions and two lab-scale RO productions

revealed only very small increases in total CFU/ml during the 4.5 to 8 hours productions.

The Illumina sequencing results provided identification of the microorganisms (both living and dead cells)

present in the samples and a relative distribution of these. These results revealed that the microbial

composition was dominated by especially, Thermus spp. and Pseudomonas spp.. Furthermore, it can be

concluded that the microbial composition varies markedly between production days as well as between the

samples taken during the production.

The majority of microorganisms isolated and identified in heat-treated UF and RO concentrates were

dominated by the Gram-positive and catalase-positive M. lacticum. In the RO concentrates made from raw

skim milk, the microflora shifted towards a more diverse flora. The flora also comprised Gram-positive

bacteria (e.g. M. caseolyticus, S. aureus, E. faecalis L. lactis and Leu. lactis). Several different Gram-negative

bacteria such as E. fergusonii and Shigella spp., were also isolated, which was expected due to the lack of

heat-treatment.

Two isolates of M. lacticum were selected for the thermal inactivation experiments, due to its presence in

both the UF and RO concentrate including its thermoduric ability to survive pasteurization processes.

Furthermore, the bacterium has been found to possess both proteolytic and lipolytic activity and therefore,

suggested to be an important indicator of the microbial quality of the raw milk.

Since the inactivation studies were carried out using raw RO skim milk concentrates, a degree of uncertainty

was naturally implied due to the interfering background flora. Therefore, it is necessary to consider this

aspect when interpreting the results. However, the thermal inactivation experiments did show inactivation

of the two isolates at different rate 62oC, 67oC and complete inactivation at 72oC after 30s in all the samples.

Furthermore, the magnitude of the inactivation during the thermal treatment seemed to be markedly

influenced by the dry matter contents in the RO retentates. This supports the theory that increasing dry

matter contents may also increase the heat resistance of bacteria.

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6. Future perspectives

The work of this thesis has provided an overview as well as a characterization of the microbial community in

RO concentrates made from both heated and raw skim milk. Furthermore, this study has also contributed to

the understanding of thermal inactivation of specific bacteria normally found in commercial RO skim milk

retentates including their heat-resistance in RO skim milk concentrates.

As mentioned earlier, the thermal inactivation trials were conducted using raw skim milk as medium. This

meant that a degree of uncertainty was naturally connected to the results. Therefore, in order to verify the

validity of the inactivation kinetics, it would be appropriate to repeat the trials with either heated or micro

filtrated skim milk. Thereby, the bacterial load would be reduced substantially including the risk of interfering

microorganisms which could improve accuracy results. Furthermore, the two selected isolates of M. lacticum

were inoculated as a cocktail to the concentrate samples. In order to investigate the potential differences in

the thermal inactivation between the two isolates, trials using only a single isolate at a time should be

conducted. The thermal inactivation showed a little inactivating effect at 57oC but complete inactivation at

72oC. Therefore, other temperatures within this interval should also be investigated. This would provide more

information about the thermal inactivation kinetics of M. lacticum and help validating the results obtained

in this study.

Another aspect which was not investigated in this study was the ability of the bacteria to grow in the

concentrates during storage. This is important since Rosenberg (1995) reported changes such as increasing

lactose and minerals, changes in pH, ionic strength and accumulation of inhibitory compound to occur in UF

milk. Furthermore, it is a possibility that the influence of these changes may be even more pronounced in RO

concentrate compared to UF. Reduced growth of bacteria is wanted if the concentrates is supposed to be

stored or transported for an extended period of time. However, if the concentrate is supposed to be used in

a cheese production it is important that the activity of the starter-culture as well as the ripening processes

are affected (Kumar et al., 2013).

During the second RO productions trial, a decrease in CFU/ml was observed similar to the observations by

Sørensen (2017). It has been shown that cultures exposed to shear stress for extended periods of time result

in increased numbers of clusters but with fewer individual bacteria. (Partrício et al., 2014; Sørensen, 2017).

Sørensen, (2017) proposed that the processing condition during the RO filtration process would either caused

lysis of the bacteria or force the bacteria together generating larger clusters with more individual bacteria.

Therefore, it seems relevant to investigate if the processing conditions (e.g. high pressure and high shear

stress) influence the microorganisms (e.g. enhancing the cluster formation of bacteria or bacterial lysis).

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Appendix

Table of Contents

1. RO membrane specifications ............................................................................................................... 89

2. RO skim milk concentrate production at UCPH ................................................................................... 90

3. CFU Total CFU/ml in milk or concentrate measured in the start and end of three RO productions at

Arinco dairy and the three RO productions trials at UCPH ................................................................. 92

4. Rep-PCR and 16S rRNA gene sequencing ............................................................................................ 93

4.1. Rep-PCR on the 44 isolates isolated from the RO concentrate collected at Arinco dairy........... 93

4.2. Rep-PCR on 30 isolates from the end of 1st RO production trial at UCPH .................................. 94

4.3. Rep-PCR on 30 Isolates from 2nd RO production trial UCPH ...................................................... 94

4.4. Isolates send for 16s sequencing – isolates from Arinco dairy ................................................... 95

4.5. Cluster-analysis based on the isolates isolated from 1st & 2nd RO production trials ................... 96

5. Illumina sequencing NextSeq .............................................................................................................. 97

5.1. Results from 1st and 2nd round PCR ............................................................................................. 97

6. Examples of calculation of heat-up and cool-down times for the milk samples in the stainless-steel

tubes .................................................................................................................................................... 98

7. Calculation of D- and z-values ............................................................................................................. 98

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1. RO membrane specifications The membrane used in this study is manufactured by Koch Membrane Systems. Wilmington. USA. The

membrane is a Dairy-Pro™ high rejecting RO element (SPIRAL.3838-RO-30)

Dimensions

Figure 31. Shows the dimension of the membrane (Dairy-Pro™ high rejecting RO element (SPIRAL.3838-RO-30)) used in the pilot RO filtration unit.

Specifications

Table 21. Overview of the membrane specifications.

Specifications

Serial number KM8038645-6030

Membrane chemistry Proprietary TFC® polyamide

Membrane area 7.1 m2

Feed spacer 0.8 mm

Maximum operating pressure 55 bars

Maximum cleaning temperature 60oC

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2. RO skim milk concentrate production trials at UCPH Table 22. Data obtained during the determination of total solids (DM) for the third RO production trial at UCPH.

Non-concentrated skim milk 15% DM

Pumice & beaker [g] 58.5 58.5 60.7 51,1 50,5 59,7

Pumice, beaker & milk-sample [g]

61.9 61.6 63.7 53.2 52.8 61.7

Weight after heating [g] 58.9 58.8 61.0 51.4 50.9 60.0

Weight of added sample [g] 3.4 3.0 3.1 2.2 2.3 2.0

Dried weight [g] 0.3 0.3 0.3 0.3 0.3 0.3

% TS 10.0 9.4 9.4 13.5 14.6 14.4

Average

9.6 14.2

20% DM 25% DM

Pumice & beaker [g] 60.3 54.0 61.9 54.0 61.7 62.0

Pumice. beaker & milk-sample [g]

62.4 56.2 64.0 56.2 63.9 64.4

Weight after heating [g] 60.8 54.5 62.4 54.6 62.3 62.6

Weight of added sample [g] 2.1 2.2 2.1 2.2 2.2 2.4

Dried weight [g] 0.5 0.5 0.5 0.6 0.5 0.6

% TS 22.3 22.3 22.0 25.7 24.8 24.7

Average

22.2 25.1

30% DM

Pumice & beaker [g] 52.8 60.5 52.0

Pumice. beaker & milk-sample [g]

55.0 62.6 54.2

Weight after heating [g] 53.4 61.1 52.7

Weight of added sample [g] 2.2 2.1 2.2

Dried weight [g] 0.6 0.6 0.6

% TS 29.4 29.4 29.1

Average 29.3

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Calculated dry matter contents:

𝑇𝑆 = 𝑚2− 𝑚0

𝑚1− 𝑚0∗ 100% (10)

Using the data from the first measurement at 30% DM:

𝑇𝑆 =53.4−52.8

55.0− 52.8 ∗ 100% (11)

𝑇𝑆 = 29.4% (12)

Table 23. The calculated dry matter replicates including averages for each of the RO production trials carried out at UCPH. P-values were calculated in order to determine statistical differences between the productions.

Desired DM 1st production 2nd production 3rd production P-value (p<0.05)

9% 9.9 9.3 10.0

9.9 9.3 9.4

9.4 9.4

Average 9.9 a 9.3 a 9.6 a 0.07

15% 13.9 14.5 13.5

14.0 14.7 14.5

14.7 14.4

Average 13.9 a 14.6 a 14.1 a 0.15

20% 21.9 21.7 22.3

21.2 21.9 22.3

22.0 22.0

Average 21.6 a 21.9 a 22.2 a 0.11

25% 24.9 25.6 25.7

25.0 25.7 24.8

25.8 24.7

Average 24.9 a 25.7 a 25.1 a 0.12

30% x 29.5 29.4

x 29.5 29.4

29.7 29.1

Average

29.5 29.3 0.18

*Values in the same row not marked by the same capitals are significantly different using one-way ANOVA p<0.05

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3. CFU Total CFU/ml in milk or concentrate measured in the start and end of three RO

productions at Arinco dairy and the three RO productions trials at UCPH

Table 24. Overview of the counted CFU/ml for the start and end of all three RO productions at Arinco (pasteurized milk) and the three production trials at UCPH (raw skim milk). For all samples two separate dilutions rows were made.

Total CFU/ml in milk or concentrate measured in the start and end of three RO productions at Arinco and the

three productions trials at UCPH

Time Dilutions:

1.00E-02 1.00E-03 1.00E-04 1.00E-05 1.00E-06 1.00E-07

1st prod Start 102 >300 18 18 4 1

End >300 >300 38 29 3 2

2nd prod Start 43 42 4 4 2 n.d.

End 59 54 3 2 n.d. 1

3rd prod Start 106 110 32 37 1 3

End >300 >300 77 68 5 7

1st trial Start >300 >300 >300 >300 >300 >300

End >300 >300 >300 >300 >300 >300

2nd trial Start

>300 >300 87 57 23 26 1 1

End >300 >300 98 96 20 27 2 3

3rd trial Start >300 >300 40 42 9 12 0 1

End >300 >300 >300 >300 46 64 7 9

*n.d.: none detected

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4. Rep-PCR and 16S rRNA gene sequencing This section shows the pictures taken of the gels after the rep-PCR DNA fragments have been separated

during the gel-electrophoresis.

An example of a gel which was used to show that the amplification 16S rRNA gene was successful is also

included. The pictures are sorted according to which RO concentrates the isolated were isolated from; Arinco

dairy. 1st production trial and 2nd production trial.

4.1. Rep-PCR on the 44 isolates isolated from the RO concentrate collected at Arinco dairy.

Figure 32. Picture of rep-PCR gel used to separate the DNA-fragments from the isolates isolated from the RO concentrates collected at Arinco dairy.

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4.2. Rep-PCR on 30 isolates from the end of 1st RO production trial at UCPH

Figure 33. Picture of rep-PCR gel used to separate the DNA-fragments from the isolates isolated from the RO concentrates collected during the 1st RO production trial at UCPH.

4.3. Rep-PCR on 30 Isolates from 2nd RO production trial UCPH

Figure 34. Picture of rep-PCR gel used to separate the DNA-fragments from the isolates isolated from the RO concentrates collected during the 2nd RO production trial at UCPH.

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4.4. Isolates send for 16s sequencing – isolates from Arinco dairy

An example of a typical eletctrophoresis-gel showing the amplified 16S rRNA gene prior to sequencing at

Macrogen.

Figure 35. Shows the gel which was used to show that the amplification of the 16S rRNA gene was succesful before the samples were send for sequencing at Macrogen. A single band at approx. 1650bp indicates a successful amplification.

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4.5. Cluster-analysis based on the isolates isolated from 1st & 2nd RO production trials

Figure 36. Complete cluster-analysis based on the isolates from 1st and 2nd RO production trials at UCPH using raw skim milk. The species names are obtained from the subsequent 16S rRNA gene sequencing and BLAST search

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5. Illumina sequencing NextSeq

Table 25 shows the barcode-primer set-up for UF and RO-samples

Table 25. Barcode-primer set-up for UF and RO-samples. ST and SL indicate whether the samples were collected in the beginning or end. 1-23 indicates the day of production and 1-2 defines the replicate umber. Note: For the first three UF-production days no replicates were made. For samples ST-3-1 & -2 and SL-2 & -1 DNA was collected directly from the PCA plates.

Library

1

UF-

samples

Library

2

RO-

samples

N715 N716 N7118 N7119 N7120 N7118 N7119

S501 ST12 SL151 SL191 SL211 SL231 S501 ST11 ST31

S502 SL12 SL152 SL192 SL212 SL232 S502 ST12 ST32

S503 ST13 ST161 ST201 ST221 ST-3-1 S503 SL11 SL31

S504 SL13 ST162 ST202 ST222 ST-3-2 S504 SL12 SL32

S505 ST14 SL161 SL201 SL221 SL-2-1 S505 ST21 Blank

S506 SL14 SL162 SL202 SL222 SL-2-2 S506 ST22

S507 ST151 ST191 ST211 ST231 S507 SL21

S508 ST152 ST192 ST212 ST232 S508 SL22

5.1. Results from 1st and 2nd round PCR

A typical gel showing the difference in fragment-size between first and second PCR during the Ilumina

preparation step.

Figure 37. A typical gel showing the difference in fragment-size between 1st (column 2 & 3 from left) and 2nd (column 4 & 5 from left) PCR during the Ilumina preparation step. The difference indicates that the adaptor including the barcodes have succesfully attached to the 1st PCR products

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6. Examples of calculation of heat-up and cool-down times for the milk samples in the

stainless-steel tubes

Biot-number (Nbiot):

𝑁𝐵𝑖𝑜𝑡 =ℎ𝑑𝑐

𝑘 (13)

𝑁𝐵𝑖𝑜𝑡 =500

𝑊𝑚2°𝐶∗0.002𝑚

0.59𝑊𝑚2°𝐶

Units on (14)

𝑁𝐵𝑖𝑜𝑡 = 1.6 (15)

𝑇𝑎−𝑇

𝑇𝑎− 𝑇𝑖= 𝑒

(−−ℎ∗𝐴∗𝑡

𝜌∗𝐶𝑝∗𝑉) (16)

Calculation of the temperature inside the tube after 30s in 72oC heated water-bath:

72𝑜𝐶−𝑇

72− 4𝑜𝐶= 𝑒

(−−500

𝑊𝑚2

°𝐶∗0.0015𝑚2∗30𝑠

1032.5𝑘𝑔

𝑚3∗3884.3

𝐽𝑘𝑔𝑜𝐶

∗1∗10−6𝑚3)

(17)

𝑇 =

(

𝑒(−

−500𝑊𝑚2

°𝐶∗0.0015𝑚2∗30𝑠

1032.5𝑘𝑔

𝑚3∗3884.3

𝐽𝑘𝑔𝑜𝐶

∗1∗10−6𝑚3)

∗ (72 − 4𝑜𝐶) − 72

)

(18)

𝑇 = 71. 8𝑜𝐶 (19)

7. Calculation of D- and z-values An example showing the calcuation of the D-value in 30% DM at 62oC

(20)

𝐷 = 1

0.0069

2.303 (21)

𝐷 = 333.8𝑠 = 5.6𝑚𝑖𝑛 (22)

(23)

𝑘 = 2,303

𝐷

𝑧 =𝑇2 − 𝑇1

𝐿𝑜𝑔 (𝐷𝑇1) − 𝐿𝑜𝑔(𝐷𝑇2)

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𝑧 = 67−62𝑜𝐶

log(5.7)−log (2.3)= 12. 8𝑜𝐶 (24)

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