How are at home fermentations without starter cultures controlled?

How are at home fermentations without starter cultures controlled?

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When making fermented food at home, particularly those that are made without the addition of a starter culture, how does one ensure that the correct types of bacteria are carrying out the fermentation? Is this generally due to the properties of the food that is fermented?

A "starter culture" is just a culture of preferred organisms. They probably differ little from local wild organisms. For example, a mixture of flour and water left to stand will (with luck) be colonized by yeast in the air that result in a serviceable yeast culture. Control of this process entails nothing more than observation over time. The environment and nature of the medium suffice to control the bugs that colonize it.

Both the Korean and Chinese versions of kimchee depend on moisture and acidity (and perhaps salinity) to inhibit unwanted molds/bacteria. The process is evidently self-controlled, but I recall seeing a film in which it was said that failure to add salt to the mixture could result in spoilage. Note that in the linked article, the author says cavalierly that one can scrape any mold that forms off the cabbage and continue with the fermentation because mold will not grow in liquid--patently false but probably "true enough" not to affect results.

Aspergillus oryzae colonizes rice, and rice with Aspergillus growth can be subjected to a secondary yeast fermentation that yields sake. The commercial production uses highly-prized starter cultures for both the mold and yeast, but it is possible to substitute other varieties of Aspergillus. For example, one can induce A. niger to grow on a citrus peel, and transfer the colony to rice. The sake that results is fine. But in this case one would want to rule out species of Aspergillus that are associated with toxins. For similar reasons some care is taken in sterilizing containers used to make wine.

In any of these processes there is a possibility of colonization by the wrong flora. The cultures are controlled by the content of the nutrients and climate and observed carefully. Over centuries there have probably been many unfortunate accidents involving unwanted organisms. There is nothing like violent illness to bring the integrity of a process into focus.

In short, the control of home fermentations lies in (1) statistical likelihood that the right organism is present in the environment; (2) the nature of the nutrient and climate; (3) the experience of the person(s) monitoring the process; and (4) luck.

How to Ferment Vegetables

Fermented vegetables begin with lacto-fermentation, a method of food preservation that also enhances the nutrient content of the food. The action of the bacteria makes the minerals in cultured foods more readily available to the body. The bacteria also produce vitamins and enzymes that are beneficial for digestion.

Almost any vegetable can be fermented, and fermenting farm-fresh produce is a great way to provide good nutrition year-round! Ferment one vegetable alone or create mix of many different kinds, along with herbs and spices, for a great variety of cultured foods. Below is what you'll need to get started.

Industrial Fermentation Processes | Microbiology

In industrial fermentations, microbial growth and product formation occur at the surface of solid substrates. Examples of such fermentations are mushroom cultivation, mould-ripened cheeses, starter cultures etc. More recently, this approach has been used for the production of extracellular enzymes, certain valuable chemicals, fungal toxins, and fungal spores (used for biotransformation).

Traditional substrates are several agricultural products, rice, wheat, maize, soybean etc. The substrate provides a rich and complex source of nutrients which may or may not need to be supplemented.

Such substrates selectively support mycelial organisms which can grow at high nutrient concentrations and produce a variety of extracellular enzymes, e.g., a large number of filamentous fungi, and a few bacteria (actinomycetes and one strain of Bacillus).

According to the physical state, solid state fermentations are divided into two groups:

(i) Low moisture solids fermented without or with occasional/continuous agitation, and

(ii) Suspended solids fermented in packed columns through which liquid is circulated.

The fungi used for solid state industrial fermentations are usually obligate aerobes (Table 39.5).

Solid-state industrial fermentations on large scale use stationary or rotary trays. Temperature and humidity controlled air is circulated through the stacked solids. Less frequently rotary drum type fermenters have been used. Solid state fermentations offer certain unique advantages but suffer from some important disadvantages. However, commercial application of this process for biochemical production is chiefly confined to Japan.

Type # 2. Anaerobic Fermentation:

In anaerobic fermentation, a provision for aeration is usually not needed. But in some cases, aeration may be needed initially for inoculum build-up. In most cases, a mixing device is also unnecessary, while in some cases initial mixing of the inoculum is necessary. Once the fermentation begins, the gas produced in the process generates sufficient mixing.

The air present in the headspace of the fermentor should be replaced by CO2, H2, N2 or a suitable mixture of these this is particularly important for obligate anaerobes like Clostridium. The fermentation usually liberates CO2 and H2, which are collected and used, e.g., CO2 for making dry ice and methanol, and for bubbling into freshly inoculated fermenters.

In case of acetogens and other gas utilizing bacteria, O2-free sterile CO2 or other gases are bubbled through the medium. Acetogens have been cultured in 400 1 fermenters by bubbling sterile CO2 and 3 kg cells could be harvested in each run.

Recovery of products from anaerobic fermenters does not require anaerobic conditions. But many enzymes of such organisms are highly O2-sensitive. Therefore, when recovery of such enzymes is the objective, cells must be harvested under strictly anaerobic conditions.

Type # 3. Aerobic Fermentation:

The main feature of aerobic fermentation is the provision for adequate aeration in some cases the amount of air needed per hour is about 60-times the medium volume. Therefore, bioreactors used for aerobic fermentation have a provision for adequate supply of sterile air which is generally sparged into the medium.

In addition, these fermenters may have a mechanism for stirring and mixing of the medium and cells.

Aerobic fermenters may be either of the:

(i) Stirred-tank type in which mechanical motor-driven stirrers are provided or

(ii) Of air­lift type in which no mechanical stirrers are used and the agitation is achieved by the air bubbles generated by the air supply.

Generally, these bioreactors are of closed or batch types but continuous flow reactors are also used such reactors provide a continuous source of cells and arc also suitable for product generation when the product is released into the medium.

Type # 4. Immobilized-Cell Fermentation:

Industrial fermentations of this type are based on immobilized cells. Cell immobilization is advantageous when:

(i) The enzymes of interest are intracellular,

(ii) Extracted enzymes are unstable,

(iii) The cells do not have interfering enzymes or such enzymes are easily inactivated/removed and

(iv) The products are low molecular weight compounds released into the medium.

Under these conditions immobilized cells offer the following advantages over enzyme immobilization:

(i) Enzyme purification is not needed,

(ii) High activity of even unstable enzymes,

(iii) High operational stability,

(v) Possibility of application in multistep enzyme reactions.

In addition, immobilization permits continuous operation of bioreactor which reduces the reactor volume and, consequently, pollution problems. Obviously, immobilized cells are used for such bio-transformations of compounds which require action of a single enzyme.

Cell immobilization may be achieved in one of the following ways:

(i) Cells may be directly bound to water insoluble carriers, e.g., cellulose, dextran, ion-exchange resins, porous glass, brick, sand etc., by adsorption, ionic bonds or covalent bonds,

(ii) They can be cross-linked to bi-or multifunctional reagents, e.g., glutaraldehyde etc.

(iii) Polymer matrices may be used for entrapping cells such matrices are polyacylamide gell, ĸ-Carrageenan (a polysaccharide isolated from a seaweed), calcium alginate (alginate is extracted from seaweed), polyglycol oligomers etc.

Comparing natural and selected starter cultures in meat and cheese fermentations

Recent literature on the use of starter cultures in food fermentation was reviewed.

Starter cultures generally improve acidification and pathogens control.

Taste and aroma are often but not always improved.

In the last decades, the inoculum of high counts of suitable microorganisms, defined as starter cultures, has become a widely adopted approach in the production of fermented foods. Here, we reviewed the recent works about the use of selected cultures or the exploitation of indigenous microbiota in the production of dry fermented sausages and dairy products. We found that the scientific literature is well consistent in indicating a significant advantage in the use of selected and natural starter cultures (SSC and NSC) as compared to adventitious microbiota (AM) in terms of acidification, sensory traits and acceptability of final ripened products, as well as in the control of undesired microorganisms. Anyway, a thorough understanding of the interactions at ecological level between the introduced strains and the autochthonous microbial communities is a challenge that needs to be addressed in the near future.

Sausage fermentation and starter cultures in the era of molecular biology methods

Fermented sausages have a long tradition originating from Europe and they constitute a significant part of the Mediterranean diet. This kind of products has a specific microbiota that is typical of the region or area where they are produced. Therefore, in order to protect the traditional aspect of these products, it is essential to understand the microbial ecology during fermentation by studying the dynamic changes that occur and to select autochthonous starter cultures that can be used in the production. In this paper we summarize the state of the art concerning the selection and use of starter cultures and ecology aspects of naturally fermented sausages. We pay particular attention to the application of bacteriocinogenic strains as they could provide an additional tool in the prevention of foodborne pathogens as well as enhancing the competitiveness of the starter organisms. Microbial ecology of fermented sausages has been determined by traditional microbiological methods, but the introduction in food microbiology of new molecular techniques complements the studies carried out so far and allows scientists to overcome the limitations of traditional methods. Next Generation Sequencing (NGS) techniques represent a change in the way microbiologists address ecology and diversity in foods. Indeed the application of metataxonomics and metagenomics will permit a detailed understanding of microbial ecology. A thorough knowledge of the mechanisms behind the biological processes will enhance meat fermentation control and modulation to obtain products with desired organoleptic properties.

Kinetic Modelling Of Wine Fermentations Biology Essay

produce high quality wines, but problem fermentations do sometimes arise.

The occurrence of stuck and sluggish fermentations pose a serious problem

leading to loss of productivity and quality. Although the precise mechanism

leading to stuck fermentations is unknown, they are often correlated with

high fructose to glucose ratios in the wine-must. S. cerevisiae is a glucophylic

yeast, indicating its preference for consuming glucose over fructose. Both these

hexose sugars are present in unfermented wine must, mostly in equal concentrations.

As fermentation progresses, glucose is consumed at a faster rate than

fructose, leading to an increase in the fructose to glucose ratio. Yeast are left

with the undesirable fructose at the later stages of fermentation, when the

environmental stresses on the yeast can lead to stuck or sluggish fermentation.

This residual fructose can lead to undesirable sweetness, as fructose is

about twice as sweet as glucose. Even with the extensive research into yeast

metabolism, there is as yet no de_nitive explanation as to why yeasts ferment

glucose faster than fructose.

This study aimed to investigate the mechanism responsible for the faster consumption

of glucose over fructose of a commercially used wine yeast strain

S. cerevisiae VIN 13. The _rst two steps of sugar metabolism, uptake and

At the start of fermentation, unfermented grape must contains approximately

equal amounts of the two hexose sugars, glucose and fructose [36]. While

both are fermented by wine yeasts to ethanol and carbon dioxide and other

metabolites, Saccharomyces cerevisiae consumes glucose faster than fructose,

being a glucophilic yeast [35]. Although fructose is used along with glucose,

the latter is consumed faster, giving rise to the discrepancy observed between

the amount of glucose and fructose consumed (G/F discrepancy). Therefore,

fermented must usually contains more fructose than glucose as residual sugar.

Fructose is the sweetest hexose sugar, approximately twice as sweet as glucose,

and therefore its e_ect on the _nal sweetness of wine is much more pronounced

[62, 27]. Residual fructose is the main cause of undesirable sweetness in dry

wines, with high residual fructose also yielding lower ethanol concentrations

and increasing the risks of microbial spoilage of the wine. Therefore, wine yeast

with a higher capability to ferment fructose are of interest to the wine industry.

During the _rst phase of fermentation, yeast cells are actively dividing, and

the G/F discrepancy gives rise to an increasing di_erence in residual glucose

and fructose [15]. As a consequence, in the _nal stages of fermentation, when

nutrients are depleted and ethanol levels are high, the yeast must ferment the

non-preferred fructose [83, 10]. Stuck or sluggish fermentation occurring under

these conditions are often associated with a high fructose to glucose ratio

[17, 41]. It is thought that the low fructose utilization capacity of S. cere-

visiae contributes to the low fermentation rate in these situations [41, 84, 87].

Problem fermentations signify a signi_cant economic loss to the global wine

industry through prolonged duration of fermentations and lower quality wines

Despite the importance of fructose fermentation to the wine industry, few

studies have been focused on this subject [15]. Glycolysis is the biochemical

pathway by which glucose and fructose are intracellularly transformed

into pyruvate, and is the main pathway yeasts utilize for sugar catabolism.

[42]. Di_erences in glucose and fructose fermentation rates may be situated

either in the di_erential transport of these sugars across the plasma membrane

or the di_erences in the hexose phosphorylation occuring inside the

cell [43, 16]. After the transport and phosphorylation steps, both glucose (as

glucose-6-phosphate) and fructose (as fructose-6-phosphate) are metabolised

via the same pathway. Both the hexose transporters and kinases have di_erent

glucose/fructose a_nities and preferences. To the best of our knowledge, the

molecular basis for the di_erence in sugar utilization by S. cerevisiae in general

In this study, an attempt was made to explain the G/F discrepancy with

a mathematical model incorporating simple enzyme kinetics. The strategy

was based on an existing model of yeast glycolysis modeled by Teusink et al.

[91]. The model had been adapted for batch fermentations, and kinetic parameters

were determined experimentally. In addition we needed to add fructose

transport and phosphorylation to the model. The metabolic pathway

of fructose di_ers only slightly from that of glucose. Both use the hexose

transporter family to transport sugars into the cell. After transport, glucose

is phosphorylated to glucose-6-phosphate and then converted to fructose-6-

phospate by phosphogluco-isomerase, whereas fructose is directly phosphorylated

to fructose-6-phosphate. Both are phosphorylated by hexokinase 1 and

2, and glucose additionally by glucokinase [6]. To validate the model, model

predicted _uxes need to be compared to real batch fermentation _uxes to assess

the e_ectiveness of modelling with measured enzyme kinetics.

This work also investigate the e_ect of sugar type on fermentation pro_les.

Does the sugar, glucose or fructose, in_uence metabolic _ux or growth if the

wine-must contains only one of the sugar hexoses.

A better understanding of the mechanism of glucose and fructose discrepancy

might help solve the problems associated with high residual fructose levels in

_nished wines. Selecting for yeast with high fructose consumption capability

are very important for the wine industry to solve problems associated with

stuck or sluggish fermentations.

The _rst and principle aim of this work was to build a kinetic model of wine fermentations

of commercially used wine yeast, Saccharomyces cerevisiae VIN13.

The approach would be very speci_c, directed on the _rst two steps of glycol

ysis, hexose transport and phosphorylation. To investigate the di_erence in

consumption pro_les of glucose and fructose, analytical techniques were combined

with computer assisted kinetic modelling. The power of this approach

is in its ability to determine the enzymatic steps within glycolysis responsible

for the faster consumption of one substrate over the other. The model could

potentially explain the di_erence in consumption pro_les on the basis of simple

kinetic constants. The model could in turn be used to aid in the construction

of models used for the screening of yeasts with desired characteristics to better

The second aim was to investigate the fermentation pro_les of batch fermentations

with only one sugar type as carbon source. The pro_les of fermentation

with 50% glucose and 50% fructose would be compared to fermentations with

either 100% glucose or 100% fructose as sole carbon source.

Brie_y, the study was comprised of the following tasks:

. Emulate wine fermentations with synthetic wine-must and a commercially

used wine yeast in a bioreactor

. Run batch wine fermentations with either glucose or fructose as sole

. Monitor substrate and product formation during fermentations

. Kinetically characterize the hexose transport and phosphorylation steps

of glycolysis with di_erent substrates in enzyme assays

. Construct a mathematical model to model wine fermentation, distinguishing

between glucose and fructose as substrates

. Validate the model in its capability to predict glucose and fructose consumption

during wine fermentations.

Winemaking has come a long way since its humble beginnings more than 7

000 years ago. Today the global wine industry is a highly competitive market,

representing a billion dollar industry. Technological innovation has insured the

rapid advancement on many of the winemaking fronts the past few decades, but

winemaking is not without problems. This review will give a brief overview of

the change in the focus are of wine research, the problem of stuck and sluggish

fermentation faced by the wine industry, and the wine yeast Saccharomyces

cerevisiae. The use of a good wine yeast strain is of cardinal importance to

the success of winemaking. With the focus of this thesis on the di_erence

in hexose metabolism of glucose and fructose by wine yeast the transport

and phosphorylation step of metabolism are also reviewed. It is the aim of

this literature review to give an encompassing overview of the wine yeast's

importance during enological fermentations.

Yeast is invariably connected to the ancient art of winemaking. The history of

winemaking dates back seven millennia, with alcoholic fermentation possibly

the oldest form of a biotechnological application of microorganisms by humans,

albeit unwittingly [85, 79]. It was only in 1863 that Louis Pasteur revealed

the role of yeast during wine fermentation, proving that it was the primary

catalyst [6]. He based his work on Antonie van Leeuwenhoek's _rst description

of individual yeast cells published in 1680 [6]. Today wine is enjoyed all

over the world, playing a major role in the economies of many countries [73].

Competition within the global market has had the e_ect of increasing diversity

and innovation within the wine industry, with the most successful wines those

meeting the prevailing de_nition of quality

A simple de_nition of fermentation is the chemical transformation of foodproducts

by microorganisms [10]. In turn, alcoholic fermentation is the anaerobic

conversion of sugar into alcohol and CO2.

This process relies almost exclusively on yeast, with the most commonly encountered

species Saccharomyces cerevisiae, known as the baker's, brewer's or

wine yeast. With the knowledge that yeast was responsible for the fermentation

process, winemakers could now control the process of winemaking. Yeasts

with improved characteristics could be selected for alcoholic fermentation. By

1890 the concept of inoculating wine fermentations with pure yeast cultures,

displaying desired characteristics, were introduced by M??ller-Thurgau, and

the quality of winemaking vastly improved [73]. The use of pure yeast inocula

insured a more rapid and reliable fermentation with consistent _avour and predictable

quality [73]. Fermentations are largely inoculated with single-strain

pure cultures added to the grape must soon after crushing [30]. This ensures

greater control over fermentations with more desirable and predictable outcomes,

greatly reducing the risk of spoilage.

During the past 25 years major advances have been made in the understanding

of the biochemistry, physiology, ecology and molecular biology of the yeasts

involved in wine making and how they impact on wine chemistry and sensory

properties adding to the appeal of the _nal product [37]. The process

of developing new strains has the main goal of achieving a better than 98%

conversion of sugar into alcohol and carbon dioxide at a controlled rate with

no development of o_-_avours [45]. S. cerevisiae has been at the forefront of

scienti_c research for decades for being a model organism for studies in genetics,

biochemistry and cell biology [26]. Not only is it of scienti_c value, but it

has tremendous economic importance in the food and beverage industries.

Up to know yeast research has mostly been following a reductionist approach,

deconstructing complex systems into smaller pathways pliable to study [26].

However, technological advances have given way to a "whole-genome" era as

opposed to a single-gene, reductionist study (Figure 2.1) [26]. Out of the

combination of whole-genome sources and computational modelling, a new

discipline of systems biology is emerging, characterized by modelling cellular

functions in such a way that realistic predictions of how the the cell will function

can be made under speci_c conditions or perturbations [26]. Being able to

have a systems-level understanding of yeast growth and metabolism has great

potential in an industrial context [26]. Computational models of genomic and

metabolic systems are already available for S. cerevisiae, with the regulation

of glycolysis having been modelled by Teusink et al.

S. cerevisiae is a model organism, having been at the forefront of research for

decades and now of systems biology research [30, 26]. Winemaking in particular

could bene_t tremendously from the applications that systems biology

research o_er, due to the impact of yeast on wine quality and production [26].

Being able to predict what e_ect speci_c mutations will have through the use

of computational models of metabolic pathways on wine production can give

rise to an array of di_erent wines from the same grapes with di_erent strains of

yeast [26]. This is of the utmost importance to stay competitive in the global

market, with wine representing a multi-billion dollar industry and consumer

demands and preferences directing the market. It is of vital importance to tailor

wine to the prevailing de_nition of quality. It is thus the aim to ultimately

provide researchers and winemakers with the ability to model the behaviour of

yeast in silico [26]. The ultimate goal is to decrease the time and cost of strain

development by incorporating a large number of designs to improve quality,

enabling winemakeres to strategically select or design new strains to tailor

wines for the consumer [26]. Past decades have seen wine research focus on

identifying and managing problems in the vineyard and winery. However, recent

years the attention has shifted to enhancing product attributes and value

Wine yeasts genetic make-up is far better understood than those of the grapevine

[74]. Wine yeasts are predominantly diploid or aneuploid, occasionally poly

ploid, with a relatively small genome and a large number or chromosomes.

They also have little repetitive DNA and few introns. The haploid strains

containt 12-13 megabases (mb) of nuclear DNA on 16 linear chromosomes,

with each chromosome 200-2200 kilobases (kb) long [73, 74]. Work for this

thesis was done on a commercially used wine yeast, S. cerevisiae VIN13. The

S. cerevisiae VIN 13 strain was engineered by Swiegers [90] to constitutively

express a carbon-sulphur lyase gene, tnaA, from Escherichia coli, exhibiting

the release of volatile thiols from Sauvignon Blanc grape juice. S. cerevisiae

has also had its genome sequenced by The Australian Wine Research Institute

Goals of wine scientists are to better understand the complex inner workings

of wine yeast to be able to develop more informed and inovative ways of developing

improved strains. With robust mathematical models describing cellular

functions it will be possible to design and trial the performance of the new yeast

strain in silico, eliminating the need of costly and time-consuming fermentations

[29, 30]. The complexity of biological systems can make the development

of novel strains a very challenging endeavour. With the use of systems biology

to understand yeast metabolism, there is the possibility of more accurately

modelling metabolic processes for better-informed manipulations to ultimately

achieve targeted and predictable outcomes.

A central goal during winemaking is the achievement of complete alcoholic

fermentation. This is however not always the outcome and the occurrence of

premature arrest of alcoholic fermentation is one of the most challenging problems

faced by the wine industry. Problem fermentations cause economic losses

through loss of fermentation space, increased duration of fermentations and

spoilage of wines. Causes of stuck and sluggish fermentations are numerous

and sometimes di_cult to pinpoint and rectify. Numerous factors can cause

problem fermentations, such as high initial sugar content, vitamin or nitrogen

de_ciencies (nutrient limitations), excessive temperatures (high or low),

enological practices, anaerobic conditions, high ethanol content, occurrence of

spoilage micro-organisms or toxic compunds (fungicides or ethanol), excessive

clari_cation of the must, presence or toxic fatty acids and high concentrations

of volatile acidity have all been linked to stuck and sluggish fermentations

[2, 17, 18]. It is therefore very di_cult to pinpoint a problem, due to the

multiple factors and the possibility of interactions between these factors [2].

Wines with high residual sugar content are susceptible to microbial spoilage

and are unacceptable for the market due to the sweetness of the wine. [17] Excessive

residual fructose in particular can compromise the quality of the wine,

as fructose is about twice as sweet as glucose and adds to undesired sweetness

Stuck, or incomplete, enological fermentations are those that, at the end of

alcoholic fermentation, leave a higher than desired residual sugar content. A

complete or "dry" fermentation is only reached when sugar levels are lower

than 0.4% (4 g/L), with typical sugar concentrations below 0.2%. Slow and

sluggish fermentations need a longer fermentation time to reach dryness, with

normal fermentation reaching dryness within 7 to 10 days, while sluggish fermentations

take considerably longer, even months to complete [17]. Slow or

sluggish fermentation is thus characterized by a low fermentation rate throughout

fermentation and stuck fermentation in turn is the premature completion of

fermentation, with higher than desired residual sugar left in the wine must [24].

Often accompanied by a high fructose to glucose ratio, it is not clear whether

the yeasts glucophilic character can lead to stuck fermentation or if it simply

accompanies it. It has been recorded that very low glucose-fructose ratio

(GFR) can lead to sluggish- or stuck fermentations [41]. When the ratio falls

below 0.1, with fructose at least ten times higher than glucose, stuck or sluggish

fermentation can occur [41]. Problem fermentations can be prohibited

with the addition of glucose to better the GFR, but the addition of glucose is

under strict legal limitations [41].

The rate of fermentations is a function of the total viable biomass as well as

the rate of sugar utilization by the individual cell [67]. When growth is limited

by factors in the grape juice and cell death occurs, sugar utilization decreases

along with a decrease of viable biomass, which can result in stuck fermentation

[17]. Sluggish fermentation can also arise when the rate of fermentation per

cell decreases with viable biomass still high [17]. It has been established that

a decrease in sugar consumption is correlated with a decrease in sugar uptake

capacity [27, 60, 65, 82, 83], while the glycolytic pathway remains functional

Free intracellular glucose is toxic to the yeast cell and so the rate of sugar

uptake must be carefully coordinated with the rates of sugar utilization and

other metabolic activities, to prevent a build-up occurring if _ux through glycolysis

downstream were reduced[17, 19, 27, 92]. Loss of transport activity in

response to environmental and physiological stress is a vital survival mechanisms

[17, 58, 65, 82, 83]. The reversal of this loss of transport is however

di_cult for the cell, which is why stuck and sluggish fermentations are so dif-

As mentioned, glucose and fructose consumption are reduced in response to

various stress conditions, impacting transport expression and activity, with the

rate of sugar entry into the yeast cell is balanced with the rate of catabolism

[19, 11]. Examples of such stress conditions are: low pH, lack of oxygen, lack of

adequate agitation, temperature extremes, presence of toxic substances, presence

of other microorganisms and imbalance of cations.

Fermentation di_culties remain a major problem, adding to production costs.

Alcoholic fermentations that cease prematurely or proceed too slowly lead to

_nancial losses due to the ine_cient utilisation of fermentor space and wine

spoilage due to the low rate or protective carbon dioxide evolution as well

as high residual sugar content [73]. General targets to improve fermentation

performance include increased resilience and stress resistance, improved nutrient

uptake and assimilation, enhanced resistance to ethanol and inhibitory

metabolites, resistance to sul_te and antimicrobial compounds and tolerance

to environmental stress factors

S. cerevisiae is an industrially important yeast, as it is inclined to perform

alcoholic fermentation even under aerobic conditions, known as the Crabtree

e_ect. Although alcoholic fermentation yields less energy than respiration it

proceeds at higher rates rapidly producing ethanol while giving the ethanol

tolerant wine yeast a competitive advantage over ethanol-sensitive organisms.

During alcoholic fermentation, hexose sugars in grape must is metabolized

to pyruvate via the glycolytic pathway, which is then decarboxylated to acetaldehyde

and _nally reduced to ethanol. The theoretical conversion during

glycolysis would yield two molecules of ethanol and carbon dioxide for one

molecule of glucose or fructose. However, that would only be in the absence of

any growth and production of other metabolites, with only about 95% sugar

converted into ethanol and carbon dioxide in real fermentation. 1% is converted

into cellular material and 4% into other secondary products[73, 27].

The most simplistic view of alcoholic fermentation is the anaerobic transformation

of hexose sugars in grape must to ethanol and carbon dioxide by yeast

and some bacteria (Figure 2.2) [98]. To begin this process, the _rst essential

step of sugar breakdown is the uptake of the sugars into the yeast cell. S.

cerevisiae uses several hexose transporters, which transport glucose and fructose

amongst other sugars, by facilitated di_usion. The two main sugars in

grape juice, or grape must, are glucose and fructose. Sucrose is hydrolyzed by

invertase in the grape berries, synthesized during photosynthesis in the vine

leaves, and yield one glucose and one fructose molecule [44]. They are therefore

present in about equimolar concentrations. Of the total carbohydrates

in the Vitis vinifera berry, 99% is comprised of glucose and fructose [3]. The

ratio of glucose to fructose is however not always 1:1, changing during fruit

maturity [88]. In overripe grapes, fructose constitutes the major sugar. In

unripe berries glucose predominates, while when berries reach maturity (ripe

stage) the glucose/fructose ratio is about 1[48, 49, 50, 52, 51].

Glycolysis is the main pathway used for sugar catabolism by yeasts [42]. With

sugar concentrations higher than 1%, catabolism is solely facilitated by glycolysis,

not entering the tricarboxylic acid cycle [5]. Glycolysis consists of 11

chemical reactions in sequence for the breaking down of hexoses to pyruvate

to release energy in the form of ATP [8]

Firstly, sugars are transported inside the cell by facilitated di_usion, from

where it enters glycolysis [60].E_cient utilization of sugars are dependent

on functional alleles of the transporters and key glycolytic enzymes, namely

hexokinase (HXK) and glucokinase (GLK), phosphoglucose isomerase (PGI),

phosphofructokinase (PFK), aldolase (FBA), triosephosphate isomerase (TPI),

glyceraldehyde-3-phosphate dehydrogenase (TDH), phosphoglycerate kinase

(PGK), phosphoglycerate mutase (PGM), enolase (ENO) and pyruvate kinase

Wine yeast is capable of fermenting various sugars to ethanol and carbon dioxide

under anaerobic or aerobic conditions [5]. They are facultative anaerobic

microorganisms as they possess the genetic equipment to metabolize sugars

aerobically or anaerobically [27]. Yeasts can therefore consume sugars through

respiration and fermentation, but at sugar concentrations higher than approximately

2 g/l, S. cerevisiae channels the sugars into alcoholic fermentation [59]

(see Figure 2.2). This e_ect is known as the Crabtree e_ect. After glycolysis,

pyruvate is converted to ethanol to regenerate the NAD+ consumed during

glycolysis and produces a net gain of two ATP molecules [9]. Enzymes responsible

for this conversion include pyruvate decarboxylase (PDC) and alcohol

The production of ethanol is not the only pathway to regenerate NAD+ although

it is the most important. The alternative pathway is glyceropyruvic

fermentation, generating glycerol as _nal product [75]. Although used to compensate

for the NAD+ de_cit in the cell, it is also produced by yeasts as a

protector against high osmotic pressures [75]. After water and ethanol, glycerol

is the third major component of dry wines, ranging in concentrations of

between 6 and 10 g/l and improves wine quality as it extends sweet and mouthfeel

Unsuccessful attempts have been made to increase glycolytic _ux in yeast by

over-expression of individual and combinations of glycolytic genes [86]. Overproduction

of the enzymes had no e_ect on the rate of ethanol formation,

indicating that the control site for glycolytic _ux under anaerobic conditions

is situated in the uptake step, with the remaining steps not appearing to be

rate limiting[27]. Therefore, the rate of alcohol production is primarily limited

by the rate of hexose sugar uptake, with the loss of transport towards

the end of fermentation resulting in reduced ethanol yields [94]. Evidently the

glycolytic pathway is tightly controlled, illustrating that sugar utilization is

already highly optimized with little room for improvement.

Glucose and fructose are the preferred sugars of S. cerevisiae. When glucose is

present, a wide range of genes involved in utilizing alternative carbon sources

are repressed, but fructose utilization is not repressed [31]. Glucose and fructose

can be consumed at the same time by yeast, although glucose utilization

is faster than fructose utilization. S. cerevisiae is a glucophilic yeast, displaying

a preference for utilizing glucose. Even though fructose is used along with

glucose, the latter is depleted _rst, giving rise to the discrepancy between the

amounts of sugars consumed during fermentation (Figure 2.4). This preference

results in a di_erence in consumption pro_les [35]. Consequently the

residual sugar left after the completion of fermentation contains more fructose

than glucose. Fructose is approximately twice as sweet as glucose, with residual

fructose having a stronger e_ect on the _nal sweetness of wine, and wine

makers often have to content with high residual fructose levels (>2 g/l), accounting

for undesirable sweetness in _nished dry wine [15, 62]. Intented dry

wines have a residual sugar level below 2g/l. Glucose and fructose are simple

reducing sugars, both mono-saccharides with the empirical formula C6H12O6,

but with di_erent structures. Grape musts total hexose sugar concentration

can range between 160 and 300 g/L[36]. Grape must usually contains about

equal amounts of glucose and fructose, but recent climatic changes are increasing

the proportion of fructose with respect to glucose in grapes[47].

The traditionally production of wine is by natural fermentation of grape juice,

with yeasts strains originating from the grapes and winery environment (natural

_ora). These strains included the genera Kloeckera, Hansensiaspora, Can-

dida, Pichia, and sometimes Hansenula, growing during the early stages of

fermentation but eventually dying o_, leaving S. cerevisiae to dominate the

rest of fermentation [13, 38, 55]. However, the desired _ora may not be established

during natural fermentations, so fermentations are inoculated with selected

yeast cultures to ensure a more rapid and predictable fermentation with

more consistent wine quality. Inoculating with a single strain of S. cerevisiae

will dominate the fermentation, out-competing unwanted natural yeast species

[13].Other members of the Saccharomyces group are also used in winemaking,

but S. cerevisiae is widely preferred for starting wine fermentations, _ttingly

known as the wine yeast. The fermentation pro_le of di_erent starter strains

has led to signi_cant improvements in the control of fermentation and quality.

Nowadays it is common practice to inoculate grape juice with a speci_c active,

dried yeast starter culture, aiding in making a predetermined style of wine [74].

Yeast development during alcoholic fermentation exhibits di_erent phases.

Yeasts metabolize sugars and nutrient present in grape must to obtain energy

for growth [27]. During the _rst few hours the cells have to adapt to the

new environment and there is no increase in yeasts population, known as the

latency or lag phase. In the second phase, the exponential growth phase or

log phase, the yeasts have adapted to the environmental conditions and begin

to grow. This phase can be in_uenced by temperature, ammonia, amino

acids and other nutrients as well as oxygen [69, 56, 81]. The yeast populationg

eventually reach stationary phase, as yeasts stop growing because of nutrient

limitations, such as nitrogen (usually not sugar), but can remain viable.

When the decline phase begin the cells have started to die because of a lack


of nutrients and the ethanol and other substances produced during alcoholic

fermentation are toxic [57]. The success of an alcoholic fermentation rests on

the viable yeast population being maintained up to the point where all the

fermentable sugars are consumed [17].

The obligate _rst step in sugar metabolism is sugar transport across the plasma

membrane into the yeast cell. S. cerevisiae is capable of accomplishing high

rates of hexose transport, with the complexity of the transport regulation re-

_ected in the large number of sugar transport genes in the genome [54]. There

is a diversity of hexose transporter genes, comprising a family encoding 20

di_erent hexose transporter-related proteins (Hxtp), thought to be involved

in transport and regulation [54]. The need for such a vast number of similar

hexose transporter proteins can be explained by the broad range of sugar

concentrations the yeast is exposed to under natural conditions. To adopt to

these varying environments require the transporters to be di_erentially regulated,

with the proteins having speci_c individual characteristics and transport

kinetics [77]. During fermentation of fruit juices dramatic changes is seen in

the physicochemical environment, and to sustain growth yeasts have to adapt

to these changes. Sugar concentrations may decline from 1 M to 10. 5 and the

overall composition of the medium changes, and the sugar transport activity

of the cell that mediate sugar transport need to be responsive to these changes

The hexose transporters transport glucose, fructose and mannose by passive,

facilitated di_usion along the sugar concentration gradient. Two uptake mechanisms

have been proposed for yeast: high-a_nity and low a_nity-uptake, operating

under low and high external sugar concentration respectively [20, 21].

These are two kinetically distinct systems, with the high-a_nity system having

a Km of about 1 mM for glucose and 6 mM for fructose, and the other

constitutive low-a_nity system a Km of about 20 mM and 50 mM for the

two sugars respectively [20]. Although the existence of the low-a_nity component

has been questioned by some. It has been suggested that the low-a_nity

transport is nothing more than di_usion of the sugar through the plasma membrane

or uptake by a more or less unspeci_c pore [39, 40]. The a_nity of the

transport system is seemingly always higher for glucose than for fructose, with

the maximum velocity of transport of fructose generally higher than that of

The multigene family of transporters of S. cerevisiae are called the hexose

transporter (HXT) genes [19, 25, 54, 53]. The HXT family is comprised of 18

members (HXT1 to HXT17 and GAL2) with high identity in coding sequence

(65% - 99%) sharing common functional motifs and secondary structure with

the same structural features of 12 membrane spanning domains [19, 25, 54, 60].

There are also two glucose sensors Snf3p and Rgt2p that are closely related

to the transporters. It has been shown that Hxt1-Hxt4, Hxt6 and Hxt7 are

the major hexose transporters for transporting glucose, fructose and mannose

[78, 77]. Hxt6 and Hxt7 are high a_nity carriers (Km 1-2 mM for glucose),

Hxt2 and Hxt4 display intermediate a_nity (Km for glucose 10 mM) and Hxt1

and Hxt3 are low-a_nity carriers (Km values for glucose 100 mM and 30-60

mM, respectively) [77, 64]. The key regulator of HXT gene expression is glucose

itself [19, 99, 96, 97]. Genes are regulated by both glucose induction and

glucose repression. Transport genes regulated by glucose induction are not

expressed in the absence of glucose whereas repressed genes are not expressed

at high glucose levels, and becoming derepressed upon glucose depletion.

Expression of high-a_nity hexose transporter proteins is dependent on the

presence of hexokinases and an active SNF3 gene and is repressible by glucose.

The low-a_nity uptake is a constitutive, kinase-independent facilitated di_usion

process[21, 22, 61, 76]. In media with high concentrations of sugar, cells

only exhibit low-a_nity uptake[66].

During alcoholic fermentation the most physiologically relevant hexose transporters

(Hxt1-Hxt4, and Hxt6/7), accepting both glucose and fructose as substrates,

have distinct expression patterns [77, 72]. Not only do they di_er in

kinetic characteristics, but also in expression patterns [100]. During alcoholic

fermentation yeast faces an ever changing environment, with sugar concentrations

dropping and ethanol content increasing. Throughout the fermentation

yeast adapts its hexose carrier expression to ensure optimal hexose transport

with respect to the environmental and physiological conditions [63]. It is the

low-a_nity carriers Hxt1 and Hxt3 that play a predominant role during fermentation.

Hxt1 is expressed at the beginning of fermentation to ensure initial

sugar uptake during the growth phase, whereas Hxt3 is expressed throughout

fermentation, with maximal expression at the point of growth arrest, decreasing

during stationary phase. The high a_nity carriers Hxt6 and Hxt7 are

expressed at the end of alcoholic fermentation with Hxt2 involved in growth

Sugar uptake and assimilation a_ects fermentation performance of starter cultures.

Sugar uptake appears to limit complete sugar utilisation during vini_-

cation and is in_uenced by factors such as ethanol concentration and nitrogen

availability [74]. It is of vital importance that the grape sugars are e_ciently

utilised by S.cerevisiae with a rapid rate of glycolytic _ux relying on functional

alleles of the glycolytic enzymes [73]. The hexose transporters, both

low-a_nity and high-a_nity, play important roles during the course of fermentation

[63]. Since wine yeasts are glucophilic it may be possible that

overexpressing transporters together with fructose-speci_c transporters (from

fructophilic yeasts such as S. pasteurianus and Zygosaccharomyces bailii ) will

help alleviate the occurrence of stuck fermentation [74].

In a study done by Guilaume et al. [43] it was found that a mutated HXT3

allele enhanced fructose utilization in S. cerevisiae. Expression of the allele

alone increased fructose utilization during fermentation, and the glycolytic

_ux increased with the overexpression of the mutant gene. This work demonstrated

that it is possible to alter the pattern of fructose utilization during

fermentation and the importance of the hexose transporter in determining the

glucose/fructose utilization ratio.

After transport of glucose and fructose into the cell they are rapidly phosphorylated

by the hexose kinase family of enzymes into glucose-6-phosphate and

fructose-6-phosphate respectively[42]. This is the _rst irreversible step of glycolysis

[32]. Glycolysis is a sequence of 11 chemical reactions breaking down

high energy hexoses for the release of Gibbs free energy in the form of ATP [7].

This _rst reaction uses ATP and is important in keeping the intracellular free

sugar concentrations low (<2.5mM), favouring continuous transport of sugars

into the cell [80]. The family of hexokinases in S. cerevisiae are glucokinase

(Glk1), hexokinase 1 (Hxk1) and hexokinase 2 (Hxk2) [80]. Glk1 can phosphorylate

glucose, wherease the two isoenzymes Hxk1 and Hxk2 are able to

phosphorylate glucose as well as fructose [32]. Hxk1 and Hxk2 share a high degree

of homology (77% identical amino acids) with glucokinase being less than

40% identical to either. The two hexokinases di_er in their glucose/fructose

preference despite their high degree of sequence similarity. Hxk1 has a higher

Vmax with fructose over glucose (threefold), while Hxt2 has a slightly higher

Vmax for glucose than fructose [14, 33]. The a_nity of Hxk1 for glucose (Km =

0.12 mM) is higher than for fructose (Km = 1.5 mM), with Hxk2 also having

a higher a_nity for glucose (Km = 0.25 mM) than fructose (Km = 1.5 mM)

During the _rst phase of fermentation, when cells are growing, HXK2 expression

is the highest. In the second phase, where cell growth is much lower,

HXK2 expression drops and HXK1 and GLK1 expression increases [93].

The conversion to glucose-6-phosphate is followed by the conversion to fructose-

6-phosphate by phosphoglycoisomerase (PGI). All subsequent reaction steps

are identical for glucose or fructose metabolism. Therefore there are only two

steps in the fermentation pathway, namely transport and phosphorylation, in

which di_erences could explain the glucose/fructose consumption discrepancy.

The glycolytic pathway is one of the best understood metabolic pathways in

biochemistry. It has been extensively studied, and its individual steps well

described and characterized. However, when viewed as an integrated pathway

of multiple steps, our understanding leaves much to be desired [46]. In order

to gain a better understanding of glycolysis as a whole, several models of

glycolysis in S. cerevisiae have been constructed [46]. Most of these models

use _tting of experimental data to model glycolysis, thereby describing the

metabolic system in relation to the conditions under which the data was collected

[91]. This puts a severe limitation on these models as they are only able

to describe the system under the measured conditions.

Insight into glycolysis as a whole can be achieved through modelling by describing

a complete pathway quantitatively. Such a model was constructed by

Teusink et al. [91]. It is signi_cantly di_erent to other models as it uses in vitro

measured kinetic data to describe glycolysis and was not _tted to the observed

behaviour of the pathway. The aim of the Teusink model was to test if an in

vivo system could be described in terms of the in vitro determined kinetics of

its individual components. Most modelling papers aim to describe metabolic

behaviour without reference to the molecular mechanisms. Simpli_ed kinetic

equations are used and rate constants _tted until the model reproduces the

observed behaviour of the pathway. For the Teusink model, enzyme kinetics

were experimentally determined from the same yeast source under the same

conditions while refraining from adjusting parameters to obtain best _t.

However, this approach has its own set of disputes for the use of kinetic properties

determined in vitro to model the behaviour of the living cell. The conditions

in the living cell may be very di_erent to conditions in a test tube [70].

As for regulation, the activity of enzymes controlled by metabolites produced

elsewhere in the cell can be overlooked, and enzymes usually found in de_ned

compartments may be subcompartmented due to binding to other structures

such as membranes, cytoskeleton or other enzymes [70]. The concentration of

enzymes is also much higher in a living cell than in the test tube experiment.

Furthermore, all kinetic data to be used must be obtained under the same

Mathematical modelling of glycolytic pathways can be an important tool in

metabolic engineering. Metabolic engineering is the targeted improvement of

the cellular properties achieved from the interplay of theoretical analysis, relying

on biochemical information, and the application of optimizing genetic

and regulatory processes through genetic engineering [4]. It makes use of a

directed, rational approach which can only be done with an in-depth understanding

of the cellular system in question. The ultimate goal of metabolic

engineering is to increase the production of valuable or targeted substances on

an industrial scale in a cost e_ective manner.

Kinetic models are built on the description of individual reaction steps within

a pathway. Enzyme characteristics are used to describe kinetic behaviour.

Kinetic equations with kinetic parameters are used to construct ordinary differential

equations (ODE's). ODE's can then be integrated over time to model

changes in metabolite concentrations. The output of these mathematical models

give changes of metabolite concentrations over time in relation to biochemical

S. cerevisiae was grown from glycerol stocks kept at -80??C by streaking out

on YPD agar plates (2% glucose, 2% agar, 2% peptone powder, 1% yeast

extract). YPD plates were incubated at 30??C for _ 48 hr before single colonies

were picked for growth in liquid media. Pre-cultures were grown in YPD liquid

media (2% glucose, 2% peptone powder, 1% yeast extract) in erlenmeyer _asks

on a shaking incubator (30??C, 125 rpm). The densities of the cells in culture

were determined spectrophotometrically by measuring optical density (OD) at

To characterise an alcoholic wine fermentation, small scale batch fermentations

were completed with wine yeast strain S. cerevisiae VIN 13 on arti_cial wine

must MS300. Growth of the yeast as well as the consumption and production

pro_les under batch fermentation conditions were monitored. This was

done with OD600 readings for growth and High Performance Liquid Chromotography

(HPLC) samples for metabolic _uxes. Biomass readings were also

included to get an relationship between OD and dry weight. The consumption

of glucose and fructose as well as the production of ethanol and glycerol were

determined with HPLC. To simulate oenological fermentations, the sugar composition

of the synthetic wine must consisted of 50% glucose and 50% fructose

(50/50 fermentation). Two 50/50 fermentations were completed and pro_led.

Synthetic wine must MS300 (20% wt/vol hexose sugar) was used as medium

to simulate a standard grape juice for batch fermentations [12]. The medium

composition was obtained from the Institute of Wine Biotechnology, Stellenbosch

University, South Africa. It contained the following components

(expressed per liter): glucose 100g, fructose 100g, citric acid 6g, D-L malic

acid 6g, mineral salts (mg): KH2PO4 750, KH2SO4 500, MgSO4 _ 7H2O 250,

CaCl2 _ 2H2O 155, NaCl 200, MnSO4 _ H2O 4, ZnSO4 4, CuSO4 _ 5H2O 1, vitamins

(mg): Myo-inositol 20, nicotinic acid 2, calcium panthothenate 1.5, thiamine

hydrochloride 0.25, pyridoxine hydrochloride 0.25, biotin 0.003, anaerobic

growth factors: ergosterol 15 mg, sodium oleate 5 mg, Tween 80 0.5

ml, nitrogen source: 120mg/L N ammoniacal nitrogen (NH4Cl 0.46 g) and

amino acids (mg): L-proline 612.61, L-alanine 145.30, L-glutamic acid 120.43,

L-serine 78.54, L-threonine 75.92, L-leucine 48.43, L-aspartic acid 44.51, Lvaline

44.51, L-phenylalanine 37.96, L-isoleucine 32.73, L-histidine 32.73, Lmethionine

31.42, L-tyrosine 18.33, L-glycine 18.33, L-lysine 17.02, L-cysteine

13.09. For fermentations with only one hexose sugar as carbon source, total

sugar concentrations were either 200 g/l glucose (100% glucose fermentation)

or 200 g/l fructose (100% fructose fermentation). For a normal 50/50 fermentation,

concentrations were 100g/l glucose and 100g/l fructose.

Batch fermentations were performed in 1 L BioFlo 110 reactors (New Brunswick)

at 30??C, 100 rpm, anaerobic, until all fermentable sugars were depleted, ranging

between 50 and 100 hours. Cell growth was monitored with OD600 readings

YPD pre-culture were used to inoculate diluted synthetic media MS300 (50%

water, 50% media). Cells were grown to mid-exponential phase (OD600 between

4 and 6) in YPD before inoculating diluted synthetic starter cultures

with an OD600=0.1 (0.83- 2.5ml) and grown in erlenmeyer _asks (volume 50-

100ml). Cells were again grown to mid-exponential phase (OD600 between 4

and 6) and used to inoculate the bioreactor to a starting OD of 0.1 (13.3-20ml).

Synthetic media volumes were 800 mL in bioreactors.

In order to follow sugar consumption and ethanol and glycerol production

rates, external metabolite concentrations had to be determined for the duration

of fermentation. HPLC was used to determine the concentrations. For

HPLC, 2 ml samples were taken from bioreactor throughout the course of fermentation.

The sample was centrifuged (14000 rpm, 5 min, 4C) whereafter

1.8 ml supernatant was transferred to a fresh tube. Perchloric acid (35%) was

added (108.9 _l) and stored at -20??C for later use. When ready, samples were

thawed and potassium hydroxide (7 M) added (99 _l) and kept on ice for 10

minutes. After centrifugation (14000 rpm, 5 min, 4??C) the supernatant was

_ltered (Hydrophilic PVDF 0.45 _m Millipore millex-HV _lters) and used for

HPLC (Aminex HPX-87H column from Biorad, 65??C, mobile phase 0.01 N

Whether sugar type has an e_ect on fermentation pro_les was investigated.

This was done by changing sugar composition of the wine must to either only

glucose or fructose as the sole carbon source during alcoholic fermentation.

Batch fermentations with 100% glucose (100% glucose fermentation) and 100%

fructose (100% fructose fermentation) were performed in duplicate and pro_led

in the same way as the normal fermentations.

Literature yielded kinetic parameters for transport and phosphorylation steps

for S. cerevisiae in various conditions. [references] For this study kinetic parameters for

the uptake of sugars across the plasma membrane was determined using living

cells. Phosphorylation kinetic parameters were determined in vitro using cell

Glucose and fructose uptake assays were performed as described byWalsh et al.

[95] from the original method of Bisson Fraenkel [20]. Cells were grown in

synthetic wine media MS300 (50% glucose, 50% fructose) to mid-exponential

growth phase (OD600 between 5 and 6) in erlenmeyer _asks in a rotary shaker

(30??C, 125 rpm). Cultured cells, typically 200 mL of culture, were centrifuged

(5000 rpm, 5min, 4??C) in 50ml tubes, supernatant discarded and resuspended

in 100 mM potassium phosphate bu_er (pH 6.5). This wash step was repeated

twice. Pellet was then resuspended in bu_er to a _nal volume of 1 mL.

Biomass readings were taken for the cells grown in synthetic media. Volumes

of 20 mL were _ltered on a Millipore _lter (dried and weighed), rinsed with

water, and dried in a dessicator for two days before weighing.

Uptake was measured at glucose and fructose concentrations ranging from 1.25

to 120 mM in _nale assay volume (speci_c radioactivity, 111 GBq._mol. 1 to

1,156 GBq._mol. 1). Radiolabelled mixture (10 _L) and yeast cells (30 _L)

were preincubated at assay temperature (30??C) and then mixed and incubated

for 5 s (measured with stop-watch). Uptake of sugars by cells was terminated

by quenching with 15 ml 100 mM potassium phosphate bu_er (pH 6.5)

containing 500 mM unlabelled sugar (either glucose or fructose) kept at a temperature

below -5??C on salt-ice mixture. Cells were collected on _lters with an

additional 15 ml quenching solution. Filters were transferred to scintillation

vials containig 5 ml scintillation _uid and radioactivity was measured with a

liquid scintillation counter. The control consisted of labelled sugar added to

quenching solution at the same time as the yeast cells.

Each sugar concentration experiment was done in triplicate. Two of the experiments

were done with samples taken from cells cultures from one batch

fermentation, and a _nal one with cells cultured from a di_erent fermentation.

The hexokinases (hexokinase 1, hexokinase 2 and glucokinase) were kinetically

characterised in terms of their a_nity and maximal rate for both glucose

and fructose as substrate. The three iso-enzymes were analysed together and

the determined parameters are thus weighed averages of the individual kinases.

Cells were cultured in YPDF media (1% glucose, 1% fructose, 2% peptone powder,

1% yeast extract), typically 100 mL of culture volume, to mid-exponential

phase and spinned down (5 min, 5000 rpm, 4??C) on a centrifuge. Cell pellets

were resuspended in 2 ml extraction bu_er, containing 20 mM KH2PO4 (pH 7)

and 1 mM freshly prepared PMSF (protease inhibitor, stock: 0.1 M PMSF in

DMSO). Glass beads (0.25-0.55 mm) were prepared by cleaning overnight in

5.8 M HCl and washing 5 times in H2O and dried overnight at 30??C. One gram

of the clean glass beads was added to 1 ml of cell suspension. Samples were

vortexed for 30 seconds and kept on ice for 30 seconds alternately for 8 cycles.

Samples were centrifuged afterwards (10 min, 14000 rpm, 4 ??C) and supernatant

kept on ice for enzyme assays. Assays were performed in assay bu_er

containing PIPES (50 mM), KCl (0.1 M), MgSO4 (5 mM) and KH2PO4 (50

mM). The pH was set to 7. NADP/NADPH linked enzyme assays were performed

to determine the Vmax and Km values for the hexokinase step for either

glucose or fructose as substrate. The assays were performed at OD340 in 96

well plates (Greiner bio-one _at bottom microplates) on a spectrophotometer

(VarioSkan microplate reader, Thermo Electron Corporation). Hexokinase was

measured with 2 mM NADP, 1.5 mM ATP, 2.8 U/ml glucose-6-phosphate dehydrogenase

(G6PDH) and glucose substrate concentrations ranging between

0-10 mM. For fructose as substrate, with concentrations ranging between 0-10

mM, 2 U/ml PGI was added. All reagents and enzyme dilutions were made

Protein concentrations of cell lysate were determined with the use of the Bradford

method [28]. The protocol was adapted for use in 96 well plates, where

190 _L of Bradford reagent was added to 5 _L of sample or standard and incubated

for 15 minutes before reading the absorbance at 595 nm. The standard

was a BSA calibration curve in the range of 0-1 mg/mL.

For each substrate concentration, initial maximum reaction rates were determined

over a minimum period of 1 minute by using the slope of maximum rate

(R2 > 0.90) and the extinction coe_cient for NADPH (6.22 L. 1.mol. 1)

with the Beer-Lambert Law. The pathlength of the 100 _l assay working volume

was taken to be 3.0419 mm [71]. By plotting substrate concentration

versus corresponding maximal rates and normalised to protein concentration,

a curve was obtained. The curve was analysed with nonlinear regression,

Michaelis-Menten, to obtain binding and Vmax values.

Kinetic models aim to be virtual representations of enzyme-catalyzed reactions

of living cells, reproducing metabolism in silico. This is accomplished

by constructing a system of interdependent di_erential equations according to

the properties of the pathway and its enzymes.

Wine fermentation was described through the construction of a kinetic model.

For this project a previous model was re_ned to separately model the uptake

of fructose and glucose rather than as a single entity. The model aimed to be

capable of accounting for the discrepancy in the consumption of the sugars.

For the hexose uptake and hexokinase phosphorylation steps values were experimentally

determined with glucose or fructose as substrates. Other kinetic

parameters were taken from previous work by Teusink, Van Nuland and Abrie

[91, 68, 1]. The kinetic model was constructed in Wolfram Mathematica 8.0.

Model validation is an important part of kinetic modelling. The constructed

model uses parameters of enzymes that have been characterised in isolation to

predict the consumption and production of certain metabolites over the time

span of a batch fermentation. Through comparison of the predicted values

with experimentally determined batch fermentation consumption and production

_uxes, one can critically test whether a proposed mechanism can explain

This model is however not completely generic, needing speci_c inputs of growth

rates, cell volume and metabolite concentrations at a certain time point of

fermentation. These variable values are experimental determined during batch

In this chapter the results of the experimental and modelling investigation into

wine fermentation are presented. The results are presented in three parts wine

fermentations, kinetic parameter estimation and mathematical modelling.

In total six batch fermentation with synthetic wine must, inoculated with S.

cerevisiae VIN 13, were completed. During the wine fermentations, biomass

and external metabolite concentrations were measured.

In grape juice, glucose and fructose are present at equal concentrations. The

50/50 fermentation with 100 g/L glucose and 100 g/L fructose serves as our

reference condition. Two 50/50 batch fermentations were completed, distinguished

as Fermentation 1.1 and Fermentation 1.2

Growth of yeast cells were monitored during fermentation with optical density

measurements. An exponential curve was _tted to the experimental data

points describing exponential growth in log scale. Speci_c growth rate (_) of

Fermentation 1.1 was _ = 0.131 h. 1 and for Fermentation 1.2 _ = 0.125 h. 1.

Exponential growth phase was approximately between 10 and 15 hours, with

growth ceasing after about 40 hours.

The rate of consumption of the two hexose sugars and production of both

ethanol and glycerol was measured for the two batch fermentations (Figure 4.2

and 4.3). Both fermentations reached dryness (consumed all the sugars) between

50 and 70 hours, taking a little bit longer to consume all the available

fructose. Both fermentations had a faster consumption of glucose over fructose,

con_rming the glycophilic character of the wine yeast S.cerevsiae VIN 13.

Starting total sugar concentrations were 1043 and 1130 mM, and _nal ethanol

concentrations 1906 and 1932 mM for Fermentation 1.1 and 1.2 respectively.

Carbon balance of the two fermentations, taking into account glycerol production,

showed an 88% carbon conservation for Fermentation 1.1 and 94% for

Speci_c substrate consumption and production formation rates of the two fermentations

were very similar (Figure 4.4 and 4.5). During the exponential

growth phase (10 to 15 hours) sugars were rapidly consumed and ethanol

rapidly formed. As fermentation progressed speci_c consumption and production

In addition to the 50/50 fermentations, we also investigated the yeast's ability

to consume the individual sugars in isolation. Alcoholic fermentations were

completed for two batch fermentations with 200 g/L glucose (Fermentation

2.1 and Fermentation 2.2) and two batch fermentations with 200 g/L fructose

Optical density measurements were _tted with an exponential equation to determine

the speci_c growth rate for the di_erent fermentations (Figure 4.6).

Fermentation 2.1 and 2.2 had speci_c growths of 0.136 h. 1 and 0.122h. 1 and

Fermentation 3.1 and 3.2 speci_c growths of 0.133 h. 1 and 0.124 h. 1 respectively.

These speci_c growth rates were comparable to the 50/50 fermentations.

The consumption rate of glucose and/or fructose and production of ethanol was

monitored for the di_erent fermentations. In these experiments we investigated

the ability of yeast to consume glucose or fructose if it is the only consumable

sugar present. Metabolite concentration changes during fermentations were

monitored (Figure 4.8 and 4.9). Both the fermentation with 100% glucose and

100% fructose consumed all the sugars in approximately 120 hours. There is

no observable di_erence in either growth rates or fermentation pro_les between

single sugar fermentations.

The single sugar fermentations (glucose of fructose) showed very similar growth

curves and fermentation pro_les. However, when the single sugar fermentations

were compared to a 50/50 fermentation, di_erences in both growth and

_ux patterns were observed. Fermentations with only one sugar showed much

slower fermentation rates, taking more than twice the time from start to dryness

compared to the 50/50 fermentations. Another di_erence between fermentation

with 50/50 sugars and single sugar fermentations is the _nal cell

densities that are reached during alcoholic fermentation (Figure 4.10). The

maximal optical density measured for 50/50 fermentations is between 16 and

19 and for the fermentations with only glucose or fructose maximal OD readings

It should be noted that in the early phases of the fermentations, up to 20

hours, the speci_c growth rate for single sugar and 50/50 fermentations are

very similar. However, after 20 hours a marked di_erence in biomass variance

is observed between the two types of fermentations. The lower biomass

concentration and longer fermentation times raise the question whether the

speci_c substrate consumption rates and product formation rates are di_erent

between the two fermentation types.

Speci_c production of ethanol and the speci_c consumption of sugar was calculated

by taking the time derivative of the substrate/product concentrations

divided by the optical density at di_erent time points (mM/hour/OD). Speci

_c production rates were calculated from change in total sugar concentration

divided by optical density. Similarly production rates were calculated from

the change in ethanol concentrations divided by optical density. These data

revealed very similar trends for all the fermentations (Figure 4.11 and 4.12).

Thus, normalising for cell density shows that, although the _nal biomass concentration

is di_erent for the three fermentation types, the glycolytic _ux

through each cell is comparable.

To estimate enzyme kinetic parameters from the transport and phosphorylation

steps for glucose and fructose, enzyme kinetic assays were performed on

The term isolated is used to distinguish the enzyme kinetic experiments from

the fermentation studies in these experiments.

In rapid, zero trans in_ux experiments, radio-labelled uptake of glucose and

fructose was measured as a function of the carbohydrate concentration.

The a_nity and the maximal rate of transport for either glucose or fructose

into the yeast cell were determined by _tting a Michaelis-Menten-equation to

the experimental data of the transport rate (umol/min/mg dry weight) against

substrate concentrations (mM) (Figure 4.13). For each substrate concentration

three data points were collected two from uptake experiment from yeast

cells collected from fermentation number one and another point from uptake

by yeast cells from a second batch fermentation. The data-sets were analysed

by _tting the curve with non-linear regression using the irreversible Michaelis-

Menten equation to obtain maximal uptake rate and binding constant of the

It should be noted that quite high errors were obtained from the estimation of

the Km values. Speci_cally for the fructose kinetics we should have included

higher substrate concentrations. We now have only one point above the estimated

Km value. This leads to an inaccurate estimation of Km and Vmax value

The determined Vmax and Km values revealed a higher maximum rate for

fructose transport compared to glucose, with a higher a_nity for glucose as

Kinetics of hexose phosphorylation were measured for cells grown on 2% sugar

YPD media. For cells grown on synthetic wine-must a saturation curve could

not be _tted in a glucose phosphorylation assay. In cells grown on wine-must,

without the addition of substrate, the reaction measured occurred at maximum

velocity for a prolonged time period (> 10 min). It was thus decided to

perform the hexose phosphorylation kinetic experiment with yeast cells grown

in YPD as these cells did not give the same problem.

Kinetic parameters for the phosphorylation of glucose and fructose by the

hexokinases were obtained from NADP-linked kinetic assays.

To obtain Km and Vmax values for the hexose phosphorylation of glucose and

fructose, Michaelis-Menten kinetic equations were _tted to the kinetic data

of hexokinase rate (umol/min/mg protein) to substrate concentration (mM)

Fitting the Michaelis-Menten equation to the experimental data revealed a

higher maximal rate and a_nity of hexokinase for glucose compared to fructose

In the following section an outline is given of the model structure of glycolysis

and how it was adapted for batch wine fermentations. We adapted an existing

model of Teusink et al. [91], to include variable biomass concentrations.

The model was constructed from the enzyme kinetic rate equations and the

pathway stoichiometry, leading to a set of ordinary di_erential equations. The

original model can be obtained from the JWS Online database

An existing model of the glycolytic pathway constructed by Teusink et al.

[91] was speci_cally adapted for S. cerevisiae VIN 13 fermentations on MS300

media. The existing kinetic model was built to describe a non-growing budding

yeast (Koningsgist), under anaerobic conditions, to investigate whether the in

vivo behaviour of yeast glycolysis could be understood in terms of the in vitro

kinetics of the glycolytic enzymes. Several changes had to be incorporated

into the Teusink model to simulate wine fermentations. The extended model

had to describe growth, volume change, metabolite transport and included

experimentally determined Vmax and Km values for the hexose transport and

phosphorylation steps with either glucose or fructose.

A set of ordinary di_erential equations was used to describe the time-dependent

changes in metabolite concentrations. In this study, the model was extended

to incorporate glucose and fructose as substrates of the pathway, and the

following equations were adapted or added into the original Teusink model

A signi_cant adaptation of the Teusink model is the modelling of glucose and

fructose as two substrates, as opposed to the original single substrate. Parameters

for the uptake and phosphorylation steps for the di_erent substrates

were experimentally determined. Vmax and Km values were included and the

initial external metabolite concentrations and biomass were also incorporated.

The rest of this section describes the adaptions made to the Teusink model by

Nuland [68]. The adaptations changes the model from describing non-growing

cell glycolysis to describing a batch wine fermentation. This incorporated

changes in volume and transport in and out of the cell of substrates and products.

External metabolite concentrations of glucose, fructose, ethanol and glycerol,

were modelled as variables in our model, this in contrast to the original model

where they were parameters. Mass action kinetics for transport of products

was adopted from the Hynne et al. [46] model. The rate of ethanol and glycerol

transport was described by

P represents the metabolite concentration and KPTransport a rate constant.

During the exponential growth phase, changes in biomass and internal volume

were incorporate in the model as follows:

During exponential growth changes in biomass can be described with

Additionally the growth rate (_) was described as a piecewise function, being

equal to zero during lag and stationary phase and equal to experimentally determined

speci_c growth rate during exponential phase.

Total cytosolic volume was modelled as a compartment of the total reactor

volume. Changes in intracellular and extracellular volume during fermentation

was modelled with the Teusink assumption that protein constitutes 50%

of the dry weight biomass, and 1 mg protein equal to 3.75 ml cytosol, used to

determine total cellular volume (in ml).

With this information the change in intracellular and extracellular volume was

included. The concentration of external glucose, fructose, glycerol and ethanol

was modelled as a function of intracellular volume

P represents the metabolite, A is a sign factor, with 1 equal to transport into

the cell, and -1 for transport out of the cell. The rate of succinate production

was also adjusted by changing the rate constant with the simpli_ed equation

The transport of the two hexose sugars, glucose and fructose, across the cell

membrane occurs via facilitated di_usion [89, 61]. Reversible Michaelis-Menten

equations were used to descripe the transport of glucose and fructose into the

cell. We assume that both substrates are transported via the same enzyme

and that they act as competitive inhibitors for each other.

The phosphorylation rate of glucose and fructose by the hexokinases and glucokinase

was modelled using reversible Michaelis-Menten kinetics. Also for

phosphorylation of glucose and fructose we assume that both substrates act

as competitive inhibitors.

In our model we used the experimentally determined parameter values of

the glucose/fructose transport and phosphorylation steps, determined in this

study. Maximal enzyme rates for the rest of glycolysis were experimentally determined

for the S. cerevisiae VIN 13 yeast by Abrie [1] (See Appendix A.1).

These Vmax values were used for our model as it was determined under wine

fermentation conditions. Other parameter values we used were adopted from

An important part of any kinetic modelling study is model validation. In this

study the kinetic model was validated by comparing measured changes in external

metabolite concentrations with the _uxes predicted by the model.

According to literature the control over

glycolytic _ux is expected to be mostly situated in the hexose transport step.

To test the ability of the model to distinguish between glucose and fructose due

to di_erent kinetics for the two substrates in the transport step a simple rate

equation describing the transport step was constructed (See Appendix A.2).

Using experimentally determined kinetic parameters for the transport step

the uptake of glucose and fructose over time was modelled. Model simulation

predicted a faster consumption of fructose compared to glucose (Figure 4.16).

As was noted in the discussion of the experimentally measured transport kinetics,

there was a large error in the Km for glucose and fructose and in addition

we could not estimate the Vmax for fructose very well.

To test the sensitivity of the transport step for the experimentally measured

kinetic parameters we used model simulations at the measured values _ the

experimental error. When we used the lower Km for glucose (26.4 - 11.66

= 14.47 mM) and a higher Km for fructose (66.15 + 8.937 = 75.087) there

was a preferred uptake of glucose above fructose (Figure 4.17). Even when a

lower Km for fructose (66.15 - 8.937 = 57.21) was used glucose was preferred

Using lower Vmax values for fructose transport also had the e_ect of leading

to the preferred uptake of glucose. Lowering the uptake rate by 25% a notable

di_erence in glucose and fructose consumption rates could be observed

Experimentally determined a_nity values did not succeed in leading to the

faster transport of glucose. It would seem that even though the hexose transporters

have a higher a_nity for glucose the faster maximal uptake rate of

fructose has a more pronounced e_ect.

The ability to model the faster uptake of glucose does however lie within the

measured a_nity range when standard error are taken into account. For the

further construction of the wine fermentation it was decided to use the parameter

values that succeeded in predicting the faster consumption of glucose.

From the experimentally measured kinetic parameters for glucose/fructose

transport and phosphorylation it would be expected that S. cerevisiae has a

preference for fructose not glucose. Since a relatively large experimental error

was observed for the kinetic parameters of the transport steps it was analyzed

whether a set of parameter values exists within the experimental error that

would result in carbohydrate transport kinetics similar to those observed in the

fermentations. For this the glucose and fructose _uxes during Fermentation

1.1 were used to calculate the ratios of glucose to fructose transport during the

fermentation. Subsequently the ratio of the kinetic equations for glucose and

fructose was _tted to the observed _ux ratios, with the experimental errors as

Taking Equation 4.3.11 and 4.3.12 result in a ratio of vGlc=vFrc (assuming internal

Glc and Fru concentrations that are negligible compared to the external

constrained _t of this equation to the observed _ux ratios resulted in the following

Note that this is not a unique solution as there are more solutions possible within

the experimental error constrains that are equally good. The observed _ux

ratios can be quite accurately described with the _tted parameter values:

With the measured ratio of _uxes in the second column and the ratio of transport

kinetic rates with the _tted parameter values in the third column. In

the fourth and _fth column the glucose and fructose concentrations at the

respective time points in the fermentation are given.

The constructed model for wine fermentations was simulated with experimentally

determined metabolite concentrations and growth rates of two indepenCHAPTER

dent fermentations (Fermentation 1.1 and Fermentation 1.2). This was done

to test the ability of the model to model wine fermentation.

For use in the model, Vmax values were converted to units of mmol/min/Lcytosol.

Initial metabolite concentrations used in the simulation were taken

from experimental data. Speci_c growth rates used were experimentally determined

and initial total biomass in the bioreactor determined to be 0.8 g for

the total volume (0.8 g/800 ml).

To access the ability of the model to accurately predict batch fermentations,

experimental data and simulations are compared. Model simulation using input

values from Fermentation 1.1 was compared to concentration changes over

time of the real fermentation. This was also done for the simulation using input

from Fermentation 1.2. The model was validated with the data from two

fermentations to evaluate the ability of the model to model changes in _uxes

due to changes in growth rates and external metabolite concentrations.

From Figure 4.21 and 4.21 it can be observed that the changes made to the

Teusink model enabled the wine fermentation model to describe batch fermentation

dynamics. However, experimentally determined values and modelled

determined values of _ux did not exactly match-up. Although the overall

trend was the same for the di_erent metabolites, there were slight over or

under estimations. Model predictions of ethanol concentrations were underestimated

at the beginning of fermentation and later on slightly overestimated.

Both glucose and fructose was depleted faster in the model simulation. The

model also slightly overestimated glycerol production.

We tested the glycolytic model more extensively in terms of the role of hexose

transport and hexose phosphorylation in distinguishing between glucose and

fructose. This was done by modelling a wine fermentation with equal concentrations

of glucose and fructose as starting condition (Figure 4.22).

Changing kinetic parameter values of the phosphorylation step to equal values

for both glucose and fructose (Km and Vmax values) had no notable e_ect on

the model (Figure 4.23). However, when the transport kinetics are changes

to be the same for glucose and fructose transport (Figure 4.24) the e_ect is

evident. After this change it is not possible to distinguished between the rates

of glucose and fructose consumption. This points to the control over glycolytic

_ux residing in the hexose transport step.

This chapter discusses the three main areas of the Results chapter wine fermentation

kinetic parameters and mathematical modelling. It gives a brief

overview of the _ndings and a _nal conclusion on the project.

To test the glucophilic character of the wine strains S. cerevisiae VIN 13 we

performed a number of wine fermentations that function as our reference state.

Analysis of the consumption and production rates of external metabolites con-

_rmed the glucophilic character of the yeast glucose was consumed at a faster

Batch fermentations with 100% glucose or 100% fructose had more unexpected

results. Firstly, both glucose and fructose were consumed at similar rates i.e.

when used as a single substrate there is no di_erence between consumption of

glucose or fructose. The 100% fermentations were signi_cantly slower than the

There were marked di_erences in fermentation time (to dryness) between different

fermentations (even in duplicate experiments), and to be able to compare

them we had to work with speci_c production and consumption rates. Even

though the fermentations had di_erent times to dryness, the speci_c consumption

and production rates of all the di_erent fermentations (50/50 and 100%

glucose or fructose) was observed to be comparable. The 100% glucose or fructose

fermentation may have taken twice as long to deplete all the consumable

sugars, but the total biomass yield was only about half reached by the 50/50

fermentations. Consumption of all the sugars took longer because there are

less yeast cells to consume the sugars. Why the yeast would not yield the same

maximum biomass is unclear.

What is clear is that irrespective of the fermentation type, the speci_c _ux

through glycolysis is the same for all the cells. It is only in the case where

glucose and fructose are both given to the cells simultaneously that glucose is

consumed at a faster rate than fructose. Total sugar consumption for all the

fermentations are the same.

The hexose transport step and phosphorylation step were kinetically characterized.

Maximum velocities and a_nities were determined with either glucose

or fructose as substrates.

The determined values for the kinetic parameters for a_nity determined are

comparable to those published in literature (see Literature Review: Section

2.4.1 for comparison). The same trend of higher a_nity for glucose is observed.

Literature values are slightly less (lower Km) compared to experimental values.

However, these values are the _rst experimentally determined Km and Vmax

values of hexose transporters determined for cells grown in synthetic wine must.

Kinetic parameters for the hexose transport showed a higher a_nity for glucose,

but much higher maximum transport rate for fructose. Analysis of the

experimental data did however show high margins of error, especially for the

determined values for fructose. The graph obtained for transport rate as a

function of substrate concentrations (Figure 4.13) failed to reach a state where

the graph plateaued. To be able to more accurately determine the parameter

values higher substrate concentrations should have been added. Especially the

estimated maximum rate of fructose could be an overestimation. Adding data

points could lead to obtaining lower a_nity and maximum transport rate values.

The phosphorylation step was also kinetically characterized with regards to

either glucose or fructose as substrate. A study done by Berthels et al [16] on

hexokinase kinetic properties in S. cerevisaie VIN 13 had similar _ndings for

the a_nity of the hexokinases for the di_erent substrates. In the mentioned

study hexokinases had a higher a_nity for glucose (0.15 _ 0.01 mM) compared

to fructose (1.09 _ 0.002 mM).

In this study the transport and phosphorylation steps were only kinetically

characterized during the mid-exponential growth phase in yeast. It could be

possible that the change in expression patterns of the di_erent transporters and

hexokinases during the fermentation stages could lead to di_erent a_nities and

maximum rates. However, for this study changes in parameter values were not

The original glycolytic model by Teusink et al. [91] was changed to describe

batch wine fermentations. The mathematical model was adapted in such a

way to distinguish between glucose and fructose as substrates during wine fermentations.

With the use of parameter values _tted to the initial glucose and fructose consumption

rates during the fermentation, the model predicted the faster consumption

of glucose over fructose. These _tted parameter values fall within

the error margins of the experimentally determined values. The sensitivity of

the model to the change on these parameters was demonstrated. While the

original parameter value estimations did not succeed in predicting the faster

consumption of glucose over fructose, it was shown that it is possible to model

the faster consumption of glucose over fructose through manipulation of these

values. The values that were used in the model still had a higher a_nity for

glucose and a higher maximum transport rate for fructose. Even though intuitively

it would seem that the fructose would be consumed faster due to the

higher transport rate, it is the higher a_nity of the transporters for glucose

that leads to the faster consumption of this sugar into the yeast cell.

The model was also validated by comparing predicted pro_les with real batch

fermentations. With input from real batch fermentation into the model (initial

experimental conditions, biomass, growth rate) the expected consumption and

production rates should be the same as the rates seen in real fermentations.

Although the same trends were observed as with real batch fermentations, the

predicted rates of the model was not exactly the same as the real _uxes. The

model exceeded the real fermentation _uxes, completely consuming the sugars

The growth function of the model would be better modelled as an equation describing

growth with regards to other metabolite concentrations, for example

ethanol. This would be better than a piecewise function, as real fermentation

growth does not follow a piecewise function. Observing real growth rates (in

log scale) shows the steady decrease of the growth rate as fermentation transitions

How are at home fermentations without starter cultures controlled? - Biology

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How to Ferment Cooked Beans

Fermentation of beans and legumes is really as simple as adding a culture to cooked beans. You can use any of the following:

All of these have the bacteria, and yeasts in the case of kombucha and milk or water kefir, that can convert the starches in the legumes into a probiotic- and enzyme-rich bean dish.

Add about a tablespoon of culture to every cup of beans. Or, in the case of a powdered culture, use the recommended amount.

Once the culture is added to the beans you need to break the skins of the beans in order for the culture to penetrate past the skins and into the starch. You can mash them, similar to refried beans, or you can gently bruise them just enough to break the skins. Then you can flavor them with herbs, spices, or onions and garlic. You then allow them to culture in a sealed container in a warm place for several days.

Be careful as the fermentation process will produce gases that must be released. Be sure to keep an eye on your jars or vessels and watch for protruding lids, which are be an indicator of too much gas build-up. “Burp” the jars daily to release any gas in the vessel.

You can then eat them as an addition to a cold bean salad, served as a mashed bean dip, or as a delicious addition to salads.

Fermentation Temperature Control: Tips from the Pros

We all know it’s true, because it’s printed on the side of yeast packages — fermentation temperatures matter. Some yeast works better warm, some cold, but did you ever ponder what happens to your brew when temperatures fluctuate from warm to cold and back again? Our tipsters did and their ideas might someday help you out of a hot spot.

Brewer: Todd Ashman,Titletown Brewing in Green Bay, WI

Understanding what happens during fermentation when temperatures fluctuate better helps the brewer determine what needs to be done. The quality of the beer and vitality of the yeast both need to be examined.

The pitching temperature of wort depends on the yeast strain — some ale strains routinely start fermenting around 70 ºF (21 ºC) and others start much warmer. Fermentation is exothermic, which means it will create its own heat. Having the ability to cool the fermentation once it starts to take off is an imperative. I’ve heard of fermentations rising in temperature as much as 20 ºF (11 ºC) in six hours. The reality is if you aren’t keeping your fermenters cool, there may be a limit to what you can expect from your brewing efforts. However, since yeast growth and fermentations are exothermic and therefore generate heat, figure that the temperature within the fermenter can be as much as 8 °F (4 ºC) higher than outside of the fermenter during the early days of fermentation. So beers that are fermenting in refrigerators set at 65 °F (18 ºC) are most likely fermenting at about 72 °F (22 ºC).

If you pitch when the wort is on the cool side (below 70 ºF or 21 ºC), you face a sluggish start and leave yourself open to bacterial or wild yeast contamination. Obviously, brewing is a series of compromises — sort of a damned if you do, damned if you don’t type of practice — so be prepared.

If you have day-to-day environmental temperature changes in the 65–90 ºF (18–32 ºC) range, chances are, your beer isn’t actually cooling down that much.

The only time external temperature fluctuations may legitimately be a factor is during the first 12 hours of fermentation. If temperatures do swing drastically in these initial hours, the fermentation may become sluggish and a good deal of your yeast may drop out of suspension. The only way I could see this happening would be a major “environmental” change, like putting the fermenter in a very cold ice bath or refrigerator. This assumes that an adequate pitch of viable yeast was made and the wort was properly oxygenated.

There are a variety of methods of cooling down wort. If you just need to get the temperature down a few degrees, try applying cool towels around your carboy. If you are looking for more of a shift, immerse about half the height of the carboy into an ice bath to cool it.

Temperature will also affect the rate of growth of the yeast. If the temperature is too high, yeast growth will be too vigorous, producing an excessive demand on nutrients and your beer will be depleted in these nutrients. This can have an effect on subsequent conditioning.

In addition to this, and probably more importantly, a higher growth temperature will change the yeasts metabolism, producing a different range of by-products, which can have a major effect on flavor. If the temperature is too cool, the fermentation will be sluggish, resulting in an opportunity for the growth of contaminants, such as wild yeast and bacteria.

In terms of fermentation, lager yeasts are routinely fermented between 40–54 °F (4–12 ºC) while ale yeast is used from 55–70 °F (13–21 ºC). The optimal fermenting temperatures of yeast vary considerably.

Some ale yeasts for example, do not perform well below 65 °F (18 ºC). The Narragansett (Chico) strain is notorious for this, as well as certain Belgian and wheat beer strains. Common symptoms of fermenting too cold are stuck fermentations, poor attenuation (high finishing gravities) and off-flavors — especially diacetyl.

If you want to ferment cold, it may be necessary to acclimate your starter to a lower temperature to prevent cold shocking them. This can be done by slowly lowering the temperature of the starter the day before.

Brewer: Jesse Williams, New Albanian Brewery in New Albany, IN

Monitoring temperature and responding appropriately to shifts throughout the brew cycle, particularly during the fermentation period will make or break your beer. So, my first tip, if you do not already possess one, get yourself a thermometer! A typical bi-metal meat thermometer will suffice, but many floating and digital models are also available. Whatever thermometer you get, calibrate it to 32 ºF (0 ºC) degrees in 50/50 ice and water, and you’re ready to go.

Yeast lives and dies according to the temperature, so be aware of yours! Most strains of brewer’s yeast can survive temperatures in excess of 110 ºF (43 ºC), but it’s not a good idea to let your brew get anywhere close to that extreme. Unless your yeast strain is geared for warmer temperatures, pitching should be commenced around 70 ºF (21 ºC), with plenty of oxygen incorporated. A cold water fed garden hose and a wort chiller should get you close to this temperature.

A little clear thinking can lessen the fluctuating fermentation temperatures common in homebrewing. Never under any circumstances leave fermenting beer where the sun can get to it. UV light can skunk a hoppy beer while it’s still fermenting. A dark basement or closet that stays within a reasonable temperature range is a decent place. Yard sales and classified ads can also yield serviceable old refrigerators for the garage that make temperature controlled brewing much more convenient. Home refrigerators always have some temperature fluctuation, but a small standing thermometer can give you a good idea what’s going on in there. Any working refrigerator has less temperature fluctuation than the floor of your garage.

All right, so you still can’t control your temperatures and don’t feel like spending the money on your grandmother’s old refrigerator. You and your homebrew do have the option to coexist and cooperate with mother nature. Simply put, follow the seasonal temperatures of your climate and brew accordingly. In the warm summer months, brew crazy Belgians (in which yeasts can withstand temperatures of 80 ºF/27 ºC) and save your winter months for lagers who like it cold.

Difference between Batch Fermentation and Continuous Fermentation Process

Sl. No.Batch FermentationContinuous Fermentation
1It is a closed system.It is an open system.
2Setup is not changed from outside once the fermentation is started.Setup is changed from outside during the fermentation process.
3The process is stopped once the product is formed.The process is not stopped for the collection of the products, but it is continuously taken out from the fermenter.
4Nutrients are added only once (in the beginning) and not added in between the fermentation process.Nutrients are added many times (in the beginning and in between the fermentation process).
5Less control over the growth of the microbes and the production of desired products.More control on the growth and production.
6Environmental conditions in the fermenter will not be constant.Environmental condition in the fermenter will be kept constant.
7Turnover rate (conversion of the substance to desired product) is less.Turnover rate will be high.
8Nutrients in the fermenter are utilized in relatively slow rate.Nutrients in the fermenter are utilized in relatively fast rate.
9Microbes in the fermenter show lag, log and stationary phases.Optimum or exponential growth rate of microbes is maintained in the fermenter.
10Contents of the fermenter are removed after the fermentation process for the isolation of products.Contents of the fermenter are NOT removed for the isolation of products. Products are extracted from the overflow from the fermenter.
11The fermenter is washed and cleaned before the next step of fermentation.No such washing step required since continuous addition of nutrients and microbes are performed.
12Relatively larger size fermenters are used.Smaller size fermenter is required, since the yield is very high.
13Less close to the natural environment.More closer to the natural environment.
14Huge application in the industrial production.Limited application in the industrial production.
15Suitable for the production of secondary metabolites whose production is not associated with the growth of the microbes. Example: antibiotics.Suitable for the primary metabolites whose production is associated with the growth of the organism. Example: organic acids, amino acids.
16More common method for the large scale production of cell biomass and products.Less commonly used for large scale production.
17Easy to set-up and run than continuous culture.Not easy to setup. Require sophisticated instrumentation.
18Less initial investment required.Initial investment will be more.
19Less suitable for the production of biomass such as Single Cell Proteins (SCP).More suitable for the production of biomass (SCP).
20Labour demand is less.Labour demand is more.
21Chance of contamination is less.Chance of contamination is more
22Easy and Quick control methods.Control methods are more complicated.

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