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Glycolipids: Function and Structure

Introduction
Marine fungi are saprophytic or heterotrophic form of filamentous spore forming eukaryote microorganisms are extensively lives in the marine or estuarine ecosystem. The characterization and diversity of the marine fungi can be studied by the direct observation of morphological structure and next generation sequencing. Taxonomically characterized marine fungi are belongs to either facultative or obligate forms. Facultative forms are originally sourced from terrestrial or fresh water region but they are able to colonize and adopt with the marine habitat and the obligate are extensively live in marine ecosystem (Kohlmeyer and Kohlmeyer, 1979). The fungi are extensively reported for the several biotechnological applications industrial utilization in enzymes, natural products and agriculture biocontrol etc.
The marine fungus are taxonomically distinct (Jones et al., 2009), saline tolerant (Jennings, 1986), special biochemical properties (Damare et al., 2006). Interestingly, the marine fungi have the novelty than the obligate fungi and attracts in applications of omics (Damare et al., 2012). Generally, marine fungi can be isolated from the nutrient rich substrata such as decaying wood (harbour), coral reef (Le Campion- Alsumard et al., 1995), seagrases (Thirunavkkarasu, 2011) and mangrove ecosystem (Saravanakumar et al., 2012) and deep sea soil (Damare, 2007) are enhance distinct diversity of the obligate fungi (Sridhar, 2005). Among the marine substrate, mangrove is an second largest source for the isolation of obligate marine fungi (Ragukumar 2004). However, the biotechnological application of marine fungi differs with the terrestrial fungi due to their environmental adaptations and distributions. Many research focus on biotechnological utilization of natural products, enzymes, biocontrol, bioremediation, fuel conservation, waste management by using the marine fungi. A lot of structurally and pharmaceutically novel metabolites, isolated from marine fungi. However, this article focuses the glycollipids from the marine fungi and their properties, biological functions and applications.
Glycolipids are a structurally very heterogenous group of membrane bound compound present in all living prokaryotic and eukaryotic organisams to human cells. The term of “glycolipid” is a compound contains one or more monosaccharides glycodidically linked in to a lipid (Brandenburg and Holst, 2005). Glycolipids are an essential constituent of cellular membrane and have the remarkable biological functions of cell aggregation or dissociation act as receptor of accepter to provide the contact. Several glycolipids has important role in immune system.
Fungal glycolipidomics
The glycolipids are interesting group of the compound occurred in cell wall of animals, microbes and plant sources (Pinto et al., 2008). The fungal glycolipids are composed of a sugar units usually glucose and galatose, hydrophobic ceramides, C19 sphingoid, C-9 metyl braches and unsaturated linkages with hydroxyhexadecanoic acids (Pinto et al., 2008).
Glycoconjugates in fugal cell wall
Glycoconjugates are composed of glycoprotins, peptides, glucons, polysaccharides, phosphoric acid, phospholipids, nitrogen and glycolipid molecules and found in the cell wall. Among the defining characteristics of fungal is cell wall complex architecture. Fungal cell walls are substantially thicker than bacterial cell walls and normally make up 10-30% of the biomass. They are freely permissible to small molecules and solute transport system and signalling receptors remains in cell membrane. A different cell wall found in the fungi comparing to animals and the role of these walls includes osmotic support, selective permeability and interaction with environment (Conzalexz et al., 2009). Fungal walls consist of covalently cross linked polysaccharides of ?-glycans and Chitin and several polysaccharides are covalently cross linked through glycosidic bonds (Pinto et al., 2008).
Fungal glycolipids exterior
Generally, the glycolipid molecules are found in cell membrane of all eukaryotic cell membranes, are contain the sugar called as glycolipids besides biologically produced biosurfactants are called as glycolipids. However, all type of glycolipids are biosurfactants but not all the biosurfactants are glycolipids (Mukherjee et al., 2006; Khopade et al., 2012). Simplest glycolipids contain the one or more sugars (Fig.) and complex glycolipids such as gangliosides contain a branch chain with several sugars. Cell membranes of the fungi have the many types membrane and are assembled from four compounds such as (i) phospholipids molecules, (ii) transmembrane proteins, (iii) inerter protein network, and (iv) cell surface markers are not identical. The glycolipids are formed in the cell wall of fungi by glycosylation in endoplasimic reticulam (ER) membrane sections and transfer the Golgi complex followed by plasma membrane (Fig). These add the sugar molecules chain to lipids called the sugar coating lipids that extents the outside of fungal cells and differences were identified in glycolipids among fungal species and used as cell surface layer or marker besides glycolipids are also compound of the fatty acids contain carbohydrates, and nitrogen not phosphoric acids includes the certain compounds of the gangliosides, sulfolipids and salfatids (Pinto et al., 2008). The glycolipids are a marker for the cell identification of cell surface changes and are serving as fundamental building blocks of fungi, energy molecule or store, component of membrane constituents, signal molecule to interact the environmental compounds in through outer matrix, lectins, growth factor, and a potential factor of pathogenesis and immune responses (Hakomori, 1990; Springer and Lasky, 1991; Pinto et al., 2008). Moreover, the detail mechanism of role and properties of the glycolipids in fungus remain unclear.
Marine fungal glycolipids
Research on glycolipids from the marine resources has expanded the due attention due to its potential novelty in biotechnological applications. Muralidhar et al., (2003) have been reviewed the glycolipids from the marine resources such as algae (Lo et al., 2001), microorganisms: bacteria (Batrakov et al., 1998), fungi (Abraham et al., 1994), yeasts (Zinjarde and pant, 2002), actionbacteria (Kokare et al., 2007), sponges (pettit et al., 1999), gorgonians (Shin and Seo, 1995), sea anemones (Sugita et al., 1994), bryozoans (Ojika et al., 1997), tunicates (Loukaci et al., 2000), marine annelid (Noda et al., 1992), star fish (Sugiyama et al., 1988), sea cucumber (Higuchi et al., 1994), sea urchin (Babu et al., 1997) crinoids (Arao et al., 1999), molluscs (Yamaguchi et al., 1992), and marine crab (Asai et al., 2000).
In terrestrial Fungus, in general yeasts have glycolipids as major constituents and are not the major compound in more fungal species. However, a high Glycolipids content of 11-16% of total lipids in Blastocladiella emersonii, the major compound of glycollipid is GalDAG and Gal2DAG (Mills and Cantino, 1974). The 61- 48 % of glycolipids is found in mycelia of Macrophomina phaseoline and the lower in the sclerotia (14-62%). However the glycolipids concentrations varied according the constituents of fermentation medium. The major compound of the fungal glycolipids identified as GalDAG and Gal2DAG based structural characterization. Further the major glycolipids of fungi is glycosphingolipids and D- glucosylceramides (Weete, 1980). Galactocerebrosides has been found in fungal species, of Aspergillus miger, C.utilis and S. cerevisae (Wagner and Zofcsik, 1969). Besides the fungal species Fusarium lini, Phycomycetes blakesleeanus and mushrooms are known to produce the glycolipids (Weiss et al., 1973). Subsequently, the glycolipids are widely studied from Torulaspora delbruecki , Saccharomyes cerevisae, Candida glabrata, Kluyveromyes yarrowii, F. pedrosoi and K. polyporus (Saito et al., 2006 ; Pinto et al., 2008). The long chain sphingadinene has been first reported from Aspergillus oryzae (Fujino and Ohishi, 1976) and subsequently from Schizophyllum commune (Ballio et al., 1979), Fusicoccum amygdale (Ballio et al., 1979)), Clitocybe geotrope and Aspergillus fumigatus (Villas Boss et al., 1994), C. nebularis (Fodegel et al., 1986), A. niger(levery et al., 2000), A. versicolor (Walenkamp et al., 1999), Candida albicans (Matsubara et al., 1987), Acremonium chrysogenum (Sakaki et al., 2001), Cryptococcus neoformans (Rodrigues et al., 2000), Colletotrichum gloeosporioides ( de Silva et al., 2004), Fonsecaea pedrosoi (Nimrichter et al., 2005), Hansenula anomala (Ng et al., 1977), Fusarium sp. (Duarte et al., 1998), Histoplasma capulatum (Toledo et al., 2001), Kluyeromyces waltii (Takakuwa et al., 2002), paracoccidioides brasiliensis (Takahahi et al., 1996), Magnaporthe grisea (Koga et al., 2006), Pichia pastoris (Sakaki et al., 2001), Saccharomyces klyuyveri (Takakuwa et al., 2002), Pseudallescheria boydii (Pinto et al., 2002), Termitomyces albuminosus (Qi et al., 2002) Sporothrix schenkii (Toledo et al., 2001).
In marine fungi, very few studies are available on glycolipids of marine fungi (Table.1); the marine white rot marine fungi Nia vibrissae is producer of glycolipids with inhibitory activity, the binding of endotoxin Lipopolysaccharide (LPS) to human endotoxin receptor (Helmholz et al., 1999). Marine fungi Gliocladium roseum KF-1040 is a producer of Roselipins can inhibit the enzyme diacylglycerol acyl transferase (Omura et al., 1999; Tomada et al., 1999; Tabata et al., 1999). Glycolipids derived from marine yeasts Calyptogena soyoae, Yarrowia lipolytica are effective on degradation of hydrocarbon (Zinjarde and pant, 2002; Konishi et al., 2010). Glycolipids synthesised form filamentous endosymbiotic Aspergillus ustus has the significant antimicrobial activity (Kiran et al., 2009). Several marine fungus such as Penicillum sp. F23-2 (Sun et al., 2009), Linincola laevis (Abraham et al., 1994), Fusarium sp (Li et al., 2002) and Microsphaeropsis olivacea (Keugen et al., 1996) are significantly produced the glycolipids with unknown application.

Effect of Enzyme Concentrations on Oxygen Production

The function of an enzyme is explained by the lock and key theory: the active site of an enzyme (the lock) has a specific shape in which only the precise amount of substrate (the key) will fit – forming an enzyme-substrate complex (the product).
Catalase can speed up the decomposition of hydrogen peroxide as the shape of its active site matches the shape of the hydrogen peroxide molecule. This type of reaction is an anabolic reaction (when a molecule is broken down into smaller molecules).
Enzymes are able to increase the rate of reaction without actually being consumed in the process. Small quantities at low temperatures are able to produce results, which would normally require high temperatures and a violent reaction from any normal chemical means. Although increases in temperature may speed up the reaction, the heat will also denature the enzymes and make them unstable. All enzymes are catalysts (a substance that causes or accelerates a chemical reaction without itself being affected), and they work best at pH7.
As long as the concentration of the enzyme substrate (hydrogen peroxide) is much higher than the enzyme (catalase) concentration, the rate of reaction is directly proportional to the concentration of the catalase. This is because, as the enzyme concentration rises, the number of active sites that are available to interact with the substrate also rises; this increases the rate of product formation.
My original experiment was an investigation into how the temperature of yeast would affect their rate of respiration. However when it came to the actual experimentation we found that the volume of dye and the volume of yeast we were using was too great (resulting in the dye actually rising out of the ‘U tube’): this meant that I would have to scale these down. However, we soon found that by decreasing these volumes the results produced were very small so I decided to completely change my experiment; instead of testing temperature, I decided to change the concentrations of the yeast I was using, and see how that would have an effect on the yeast’s rate of respiration and therefore the volume of oxygen evolved.
Key Variables Concentration of yeast: The rate of respiration in yeast (and therefore the volume of oxygen evolved) may change depending on its concentration
Volume of hydrogen peroxide: I am mixing this with the yeast so the catalase will cause it to decompose into water and oxygen
Type of yeast: The rate of respiration may vary in different types of yeast
Temperature of the room: the temperature can affect the rate of respiration for the yeast depending how hot or cold it is
Type of equipment: the length of the glass delivery tube can affect the volume of oxygen evolved
Volume of yeast solution: The volume of oxygen evolved in yeast may differ depending on the volume of yeast solution
Independent Variable
Concentration of yeast: I am investigating how the volume of oxygen evolved from yeast (specifically the enzyme in the yeast – catalase) changes when the concentration of yeast suspension varies so it is important to change this variable
Controlled Variables
Volume of hydrogen peroxide: since I am already changing the concentrations of the yeast I use, I must keep the volume of hydrogen peroxide the same throughout in order to make it a fair test
Type of yeast: I must use the same type of yeast throughout: otherwise this could affect the amount of oxygen evolved in the yeast
Temperature of the room: I am going to maintain the same temperature in the room I am conducting my experiment in to try and get the most accurate result I can
Type of equipment: the size and diameter of the glass delivery tube affects how the long the test lasts – ultimately having an effect on the volume of oxygen evolved
Volume of yeast solution: I have to keep this the same if I want to get accurate results
Dependent Variable
Volume of oxygen evolved: The volume of oxygen evolved will change depending on how much concentrated yeast is being mixed with the hydrogen peroxide
My prediction:
I think that as I increase the concentration of yeast, the amount of oxygen evolved will increase proportionally: this is because as the enzyme concentration rises, the number of active sites that will be available to interact with the substrate (hydrogen peroxide) also rises – increasing the rate of oxygen evolved.
My experiment Apparatus used:
Gloss delivery tubes
Screw clip
Clamp
Rubber tubing
Litre beaker
Inverted barrel
Boiling tube
Plastic syringes
Rubber bung
Glass stirring rod
Stopwatch
Experimental Procedure
First, I used clamps to support the boiling tube and attached the rubber tubing to the barrel of the 20cm3 syringe
Then I removed the plastic syringe, leaving the needle in the same position, and removed the bung from the boiling tube
After stirring the yeast suspension (which I made by adding 10g dried yeast to 100cm3 water I prepared it one hour before I actually needed to use it), I used a plastic syringe to introduce 5cm3 of yeast to the boiling tube
I then filled the 1cm3 syringe with and placed it into position
I opened the screw clip to draw water into the barrel of the 20cm3 syringe and closed it once the barrel was full, then I injected the hydrogen peroxide into the boiling tube
I measured and recorded the volume of oxygen collected in the barrel of the 20cm3 syringe over a period of five minutes (I also used a stopwatch to measure how much oxygen was evolved per minute)
This was repeated using 10, 15, 20, 25 and 30cm3 yeast suspension in the boiling tube (with fresh samples of yeast and hydrogen peroxide)
This method was repeated for the above three times and a mean average was calculated; my results were recorded in a table (see my results)
Using the tabulated data I plotted graphs of my results before analysing them

In the above table we can see that when 5cm3 of yeast is being mixed with the enzyme substrate and an average of 4.77cm3 of oxygen is being evolved, then in theory when 10cm3 is being mixed with the enzyme substrate the volume of oxygen evolved should be double the average volume produced for 5cm3 of yeast (4.77cm3 x 2 = 9.54cm3). However, this is not the case, as actually an average of 5.33cm3 of oxygen is being evolved for 10cm3 of yeast being mixed with the hydrogen peroxide: this is because part of the oxygen evolved is actually being used by the substrate for respiration – this results in the curve of the line in graph 3 4.

Data analysis of all graphs In graph 1 a pattern can be seen in the results: the higher the yeast concentration, the greater the volume of oxygen is evolved. We can also see that towards the end of run 1 the volume of oxygen produced does not change and it becomes a straight line: this might be attributed to the fact that the yeast has become saturated with the substrate. In my scatter graph I have decided to use polynomial lines of best fit – this is because rather than a linear line of best fit (which is completely straight and does not actually show the curve/steepness of the varying results) a polynomial line actually shows the curve, and allows the viewer of the graph to see how the production of oxygen actually fluctuates and changes.
In graph 2 we can see that most of the oxygen evolved from the reaction passes into the collecting vessel within one minute of mixing the two reactants together. Afterwards the rate slows and only a small volume of oxygen is produced afterwards (particularly in between the third and fifth minutes). The pattern of oxygen evolution indicates that the reaction is extremely rapid.
In graph 3 it can be seen that as I increase the concentration of yeast the volume of oxygen evolved increases proportionally: this is because as the enzyme concentration increases, the number of active sites that are available to interact with the hydrogen peroxide molecules also rises – thus raising the production of oxygen.
In graph 4 we can see that the error bars are very small, which means that the results produced must be very accurate (as there is not much range between the different volumes of oxygen produced per yeast suspension).
Conclusion Overall, my results show that there definitely is a quantitative relationship between the concentration of yeast/catalase, and the volume of oxygen evolved: the higher the yeast concentration, the higher the volume of oxygen was evolved: this was because as the enzyme concentration rose, the number of active sites that were be available to interact with the substrate (hydrogen peroxide) also rises – increasing the rate of oxygen evolved; hence, my original prediction was correct.
Evaluation All in all I would say that my experiment was a success as I had no anomalous results (so I would not need to repeat any), and my results agreed with my prediction; my results were also substantial enough to let me draw a conclusion from them. I would say that my experiment was kept fair, however I believe that more could have been done to make sure my results were of optimum accuracy: for one I could have regulated the temperature of the laboratory I conducted my results in (maybe by having a thermometer with me and making sure that the temperature more or less stayed the same). Also, when measuring the volume of oxygen evolved per minute, the results maybe could have been more accurate (as sometimes there was a delay in pausing the stopwatch, causing more seconds to be added onto the actual time taken). However, as seen in graph 4, the error bars are very small, meaning that the accuracy of my results were very precise: this is most probably due to the fact that I repeated the experiment for each of my yeast concentrations three times so I could have lots of results to back up my prediction/conclusion.
If I had to make any modifications to my experiment, one would be that I covered a larger range (in terms of yeast concentration) so that I could have even more results to back up my conclusion; however I don’t think this would be a necessary change as I believe the results I have already firmly support my conclusion.
Sometimes when I was measuring the volume of oxygen evolved per minute (for a period of five minutes) I sometimes experienced difficulty in stopping the stopwatch as soon as one minute had passed: maybe if I had had two people timing separately for me, I could have ensured that the final recorded time was accurate. Apart from that though, the rest of my equipment succeeded in making my experiment a ‘fair test’ – the syringes had a set amount of substrate in them, thus resulting in me correctly injecting the precise volume of hydrogen peroxide each time.
I would not make any improvements to my method other than washing each syringe after use, to prevent any chance of contamination.

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