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. We were discussing on screening and selectionof the highest yielding cell line. So, what methods can be used for selecting the highestyielding cell line can be active and passive techniques . So, now coming on to the effectof other parameters like light. Now light is a crucial parameters specially for plantcells. The light intensity which means the light quality the photo periodicity whichmeans the light photoperiod cycle. Generally in in vitro cultures we keep 16 to 8 hourslight dark cycle, but it may vary people optimize photo periodicity to complete 24 hour cycleeven. When I say light quality what does it mean light intensity is one which is lux and.Wavelength of the light. Wavelength of light. So, sometimes secondarymetabolism is also found to be a function of the kind of light which means the wavelengthof light. Sometimes in some of the secondary metabolites blue light has been found to inducethe production of a secondary metabolite we will be discussing some of the examples. So,the behaviour of culture is influenced by 3 things I said photo periodicity , lightquality and intensity. Now promontory effects of light may possibly due to what becauselight might Anil literature if you see he can play a role in activity and expressionof enzymes activity of enzymes when getting affected can even lead to active transportof these nutrients uptake of nutrients from the soil or the medium.So, now this can be an indirect correlation because some of these enzymes which are responsiblefor active uptake are getting influenced their expression can be getting influenced by thelight photoperiodicity or light intensity or the kind of light or the wavelength. So,enhanced uptake of sucrose and nitrate has been reported in literature to be affectedby the light . Now I was saying an indirect effect some ofthese might lead to generation of ATP enhanced production of ATP which in turn may facilitatethe active transport of the nutrients . The process being under the controlled of phytochromes.Now these are certain kind of proteins be are proteins which are generated which areimpacted by the light which in turn may help in the transcription of the certain enzymeswhich may be responsible in the biosynthesis or induction of a particular secondary metabolitepathway . So, the process being under the controlledof phytochrome through mediation of increase in the intracellular level ATP also and ifyou will see literature they might be directly impacting the transcription process. So, contradictoryeffect of light on enhanced secondary metabolite production in the presence of light has alsobeen observed where higher accumulation happens in dark.Now if in nature sometimes a particular secondary metabolite is known to be synthesized in theunderground parts. So, now, getting synthesized in the underground parts the regulation mightbe with light. So, then if under in vitro conditions you will try to enhance the productionyou may observe that under complete dark conditions in your plant cell or other forms of in vitrocultures the secondary metabolite biosynthesis is found to be affected or regulated. So,some cues have to be obtained by how and where the secondary metabolite is getting synthesizedand under natural conditions . A temperature now coming onto temperaturegenerally 25 degree plus minus 2 is what is found to be suitable for generally most ofthe species, but sometimes even a change in 2 degrees or 3 degrees makes a differencethat is what we observed with the Bylaw Udharatha. So, there are plant growth chambers whichare maintained at 23 and a plant growth chamber which is maintained at 25 , but under 25 degreesC you will find that they are they do not grow much their growth rate gets a affected. So, therefore, temperature and again how do you think the temperature can play a rolein the growth as well as secondary metabolism how does the temperature affect .Mam presence of light is directly proportional to the (Refer time: 05:19).Light is one temperature. (Refer time: 05:24) enzyme activity.Enzyme activity can get impacted or membrane composition membrane fluidity permeabilitycan get impacted . So, there are different ways in which the temperature affects.Now, coming onto aeration and culture mixing. This is particularly important under in vitroconditions when you are working with in vitro cultures like hairy root cultures or cellcultures and when is it more useful or more crucial when it is in under liquid cultureconditions . Culture conditions.Now culture agitation and aeration these are set to be independent parameters . Now agitationis what it will facilitate like any other fermentation process it will facilitate .Mixing. Mixing is related to mass transfer homogeneity.So, not only of the it will allow the cell to be suspended does not allow it to settledown again affecting the mass transfer . What else. You said homogeneity means all the mediaaround is homogeneous in composition then. (Refer time: 06:35)Mixing everything is properly makes means uniform conditions throughout what else .In in case of plant cells. Friability.Separate cells will be. Dispersing.Dispersing. Which means settling down. So, keeping themin suspension ok. The size of the bubbles .And in shake flask there is no bubbling isn't it.. So, then we can afford to stop have a staticshape flask . Says keep on moving the cells which were onsurface they will come down and like. Or the media.Media also. Ultimately the gas to the cells is throughthe media. Hm.So, the transfer is facilitated if the media is and how is the aeration taking place ina shake flask specially it is a aeration through surface aeration . So, continues circulationwill facilitate the contact of the media with the air above . So, culture agitation andaeration are independent cultural components they can get a they can impact the growthas well as secondary metabolite biosynthesis . Now culture volume whom may have influencein oxygen absorption coefficient associated with the area of the culture medium . Culturevolume how does it impact which we also call as media to flask volume ratio because inturn it will impact the. Product.Surface to volume ratio . The surface which is exposed .(Refer time: 08:17). To the air . So, rpm generally although thisis just a range 90 to 120 rpm is if you see microbial fermentations it goes above 250rpm, but in plant cell fermentations nearly less than 100 or around 150 crossing above200 and so, then how will you find that what rpm is the optimum. If I give you to planan experiment that what agitation speed should be optimum how will you decide .It will write down the effect rpms or say. Ok.All the culture conditions and experimental set ups same and will run it on differentrpms and whatever we are aiming to increase will check for it whether it maximum productionmaximum time production. Now, why do you think there would be a change. What will get first impacted the secondary metabolite biosynthesis or .(Refer time: 09:22) It is an intern response of something else.Cells itself will get damaged. Yeah because they are very sensitive .Not very sensitive. But.Yeah, but there can be detrimental shear forces .. With increase in rpm. Now how will you thenfind or justify that this rpm. So, in turn when you talk about shear forces or shearsensitivity damage how will you quantify that. Viability cell viability.Cell viability . What are the methods did we study earlier for plant cell viability.t (Refer time: 09:56) t t c (Refer time: 09:58). Ha.Ha. Closer to that ttc assay . So, you can usethese assays to check the viability. So, percentage viability drop with the rpm and then findout because intern it is the biomass productivity which will get affected and thereby your productproductivity . So, the first would be indication would be your biomass productivity and yousee your viability ok. What else do you think apart from oxygen can also get impacted bythis media flask volume ratio or your rpm. There are other gaseous components like CO2 or volatile components which act as growth regulators specially in plant cell fermentationslike ethylene. So, now how if there is too less or too muchof rotation then this may lead to escape of these volatile components which may be neededfor the plant growth regulation . Now, pH generally plant cells they prefera little slight acidic pH which ranges between 5 to 6 . So, the ph when you maintain irrespectof the species one has to see that it between 5 to 6 they are quite sensitive which oneis the optimum pH. Now how do you think the ph impacts the growth.Age. Enzyme activity is crucially getting impactedby the surrounding pH of the medium . So, media with undefined organic components areusually buffered. So, when we use generally media media is well defined which is calledas the defined composition, but when we use complex substrates. So, there is batch tobatch. So, because breaking them down for example, your yeast extract or your peptoneor casein hydro lysate these are complex substrates. So, now, when you use such kind of complexsubstances then your pH might get affected. So, then you generally have a buffering agent.So, what are the most common buffering salts which are used in media .k h 2. Fermentation media.Potassium k h 2 4 potassium cons trait. Potassium dihydrogen phosphate .potassium dihydrogen phosphate. So, your inoculum and pre culture is alsoone of the significant factors which impacts the growth and secondary metabolite productivity. Now size generally when you optimize inoculum you optimize inoculum age you optimize inoculumsize . So, when I say inoculum age which means what.Which phase of the root. Understood. Now when you say inoculum sizewhat does it mean . How much of long how much of inoculum.Concentration of inoculum. So, that has to be optimized now secondary metabolite accumulationhas been found to be influenced by preliminary treatment. Now what preliminary treatmentif you remember I did talk about this that it is very crucial specially in plant celltechnology that what is the quality of your inoculum when I say quality of your inoculumit is not with the size . It is quality of the inoculum refers to .(Refer time: 13:28) Do you do you agree that quality of inoculumis one of the factors which can be crucial. Hm yeah.So, when I say quality of the inoculum what does it mean irrespective of any kind of fermentation.How fresh the inoculum is yes (Refer time: 13:43).So, which means age of the inoculum . What else . Where do you think your bioprocessefficiency in terms of inoculum quality how can that be impacted . Inoculum will be . Whatis the ratio of the most productive cells in your inoculum . So, which means that whenyou say age of the inoculum and the ratio of the productive cells in the inoculum.So, because always these are mixture of cells. If you take it plant cell fermentations theyare coming from callus which is a heterogeneous mass. So, you need to make sure like synchronousculture. So, when you are preparing the inoculum you need to make sure that you end up in aninoculum which is of high quality which means it has the right age and it has the most productivelarger amount of the number of cells which are required for the production of that secondarymetabolite is higher the ratio is higher than the other cells some cells may be of differentsize, shape and therefore, metabolic activity .Now, medium components we have already spoken about the different types of medium componentswhich are required in plant cell fermentations. Now generally medium can conditions whichmost frequently support when we say secondary metabolites. So, generally what is observedthat the media components which will support the growth may not be working well for thesecondary metabolite yield. So, if you need to optimize the medium composition then themedium composition has to be separately optimized for biomass and for the production of thesecondary metabolite. Now we will see how the media composition is optimized . Whenthe objective is to optimize for maximum biomass for example.So, then how will you find using single factor a range in which you should be optimizingif suppose the range is not right what kind of trend will you observe .(Refer time: 16:00). Hm.Low production. Trend you are working in a range. So, youwill see a trend isn't it what kind of trend can you observe if the range is not right.Decrease increase. Continuously decreasing or.Continuously increasing. Continuously increasing. So, it will be kindof a linear model . So, is that the right model for optimization.No. No what kind of models will end up in givingyou optimum values. Bell shaped bell curve bell shaped curve.So, what kind of models now convert them into mathematical form. What kind of equationsend up in convergence you are bell shaped. hm your bell shaped all shape (Refer time:16:45). So, what kind of 2 degree 3 degree polynomialthey will have a convergence point. Hm.Generally you do not have to go beyond that because then it becomes.Too complicated. Too complicated for optimization and the effectis also not that significant to work with and spend time and a media and cost involvedin optimization. So, you go up till 3 factor level cubic models most crucially impactingyour product yield. Now this is what is done in your statistical optimization which youpeople were talking about. Once you have done your single factor you get the suitable range.So, there are at least make sure that you end up in seeing increase and decreasing trendbell shape curve and then if you want to optimize it further then you select that range andthen use designs which are called as screening designs and then optimization designs usingdesign of experiments. Specially in bioprocess this should be takenup. This is a very useful tool which will end up where which will be used in gettingto the optimum parameters in minimum number of experiments possible and when you do singlefactor you do not end up in the right optima why . Why do you think varying one factorat a time may not give you the right optima although you will be able to find a bell.It is not. That.Because you not it does not account for production. Interaction of.Of the other all the components in the media. So, now how do you think your statisticaloptimization tools will take into account the interactive effect.well we give high and lows of each of them via component and then.Ok. Gives us a set of experiments varying different.So, a number of recipe can be designed because every factor is varying. So, they can be.So, many permutations. So, now, what is the advantage. I said the number of experimentsare minimized. So, more the number of factors it will keep on exponentially increasing.So, now, the help of these tools these are called as fractional factorial designs . Whatdoes that mean . There are full factorial designs as well, but generally to minimizethe number of experiments and get to the optimum value you use fractional factorial designsas well. What does it mean . Taking that (Refer time: 19:36).No no coming to the design right now we are designing experiments. So, which means thatamong these aid there can be different I am just giving you a small . So, now, you pickand choose the design of experiment tool we will pick and choose only some of these designpoints . Now some of these designed points points will be then given to you and you willbe asked to carry out the experiments . Now some of these designs in the range which youhave given it will choose depending on the interval there can be. So, many differentrecipes design can be which chooses only 3 points for a particular variable or designcan be which chooses 5 points for a particular variable in this range.So, there are different types of designs depending on the number of data points they choose forevery variable and then from there it chooses only set recipes and gives you a design ofexperiments the which the tool asks you to carry out. Now suppose coming back to a secondarymetabolite which is non-growth associated you will carry out the experiment what shouldbe your response for every experiment . So, your media for bio mass will it be same forthe media for your product. No.Not necessarily. Hm.So, then how would you know which component is for biomass and which component is forproduct such that ultimately you end up in maximum product productivity . So, therefore,you would like to optimize in one go how are your different media components are affectingthe biomass and how are your different media components are affecting your product becausethese may not be directly correlated. Depending on whether it is growth associatedor non growth associated product formation and also whether there is a need to do biomass separately and this also depends on whether it is extracellular intracellular productformation. Ultimately the goal is productivity . So, now, coming back to your screening designs.Now, first thing is I have some so many different media components first I need to know beforeeven I come to the optimization part which are the most significant ones . So, that Iwas talking about in the earlier classes that screening designs like Placard Barman designis most frequently used you must have heard you must have seen many papers in literature.What it does connecting it with mathematical modelling . What does it do . These screeningdesigns generally as your experimental recipe is obtained. It depends on certain assumptionslet us talk about the placard barman which is most frequently used. It is based on theassumption that although there is interaction among the factors, but at if there is an interactionbetween any 2 factors or 3 factors you cannot negate that at least one of them will be havinga very significant effect then only their interaction factors are having significanteffect isn't it. So, and what else that there is factor scarcitywhich means that the factors which you have chosen are independent factors. They are notcompounded which means the one of the component is not affecting you are not matching penwith pencils here . So, these are independent factors. So, now, with this it takes intoaccount because it assumes that the main effects are the most significant effects and becauseof these significant effects the interactive effects will gain importance .So, it neglects the interactive effect and fits it into a linear model. Linear modelmeans only taking into account the main effects main effects are the effect of each of yourparameters a b c d and it will ask you to carry out the experiments in the 2 a rangewhich you have given the lower level and the higher level it will select some of the designpoints and then you will do the experiment based on that experiment it will try to fityour response. Now your response becomes in that y is equals to mx plus c your responseis y. y.Isn't it and you are factors is x1, x2, x3 . Now it will based on the y value it willbased on whatever experiments you have carried out you will get a number of y's for numberof x1, x2, x3 function. So, you will fit all this in a linear model polynomial based onthe fitting and the closeness of the fitting it will do a simple regression analysis andit will fit and it will give you the coefficients of that m mx plus c was there. Now this mx can be m1 x1 plus m2 x2 plus so on . So, it will give you after fitting fittingis what modelling is what. Aimple you began with a simple equation y is equals to m xplus c you give the data of y and x you will end up after best fitting it we will giveyou the value of m and c similarly in the same model. It will give you the values ofdifferent m s for different x1 x2 isnt it now depending on the value of these m s andthat signs what can you make out . Positively they really making the concentrationnegatively down (Refer time: 25:50). Be more clear.. Suppose you see a positivevalue of m what does it mean . Let us talk she is talking about the sign first we willnot talk about the magnitude let us talk about the sign first a positive coefficient meanswhat . Growth rate growth field.All the time be more specific. (Refer time: 26:17).It is dependent on what it can only say be more specific that in the range which youhave selected as you increase from the lower end to the higher end it is positively impactingthe y can be any response . A negative would mean what that in the range selected as youare increasing it is negatively impacting. Now why this is important in the range selectedthis may be a major nutrient like for example, nitrogen negative does not mean that you takeaway nitrogen make it to zero. Hm.It would mean that the amount which you are currently adding or in this range which youhave chosen it can go below the minus 1 which you have chosen or the lowest limit whichyou have chosen. Ideally it should be now checked below this minimum range understood.Now talking about the magnitude what does the magnitude signify . How will it help inyour media optimization . All the factors will be given some signs of magnitude isn'tit. So, now this is this will tell you what supposethere were 3 factors one is minus 5 plus 5 plus 3 what can you do with these values . Whatcan you do with these values with magnitude can you not rank them.Yes right (Refer time: 28:03). Rank them for what ranking is what now whatwas our aim before we began with plucked barman. (Refer time: 28:12) optimization.Screening design means what not optimization. Hm.I said screening design what does that mean. (Refer time: 28:22).To choose. Which (Refer time: 28: 24).Which one is significant which one is least significant which means ranking can be done.Now for optimization if there were 16 parameters 16 components in the media all 16 will beranked. Hm.So, optimization means all 16 have to be optimized ideally on paper , but do you think that isworth spending time money consumables. Depending on this magnitude and the sign you can pickthe top ranked which are most significantly affecting your response for further optimizationin the range. Now why do you think further optimization is crucial like the values whichI gave you minus 5 which means that. Minus.You need to now see you would rather pick up minus 5 and plus 5 and leave the plus 3because minus 5 magnitude wise it is more significant which means the reduction of thiscomponent on optimization in the lower range can affect your response much more than withthe same change which you would make can affect your response much more than your plus 3 changethe same change which you would make 2 plus 3 .So, that is what is useful in screening designs then you rank them then you come on to optimizationdesigns . You must have read papers the most frequently used is your response office methodology.Response office methodology there are a number of tools there. One of the tools most frequentlyused is central composite design you must have heard about box behnken design also.So, central composite design what does it do or these a response office methodologyin general what does it do. It will have a number of tools which I was now talking aboutthat between 3 to 5 in that same range which you had given it will pick and choose therecan be any number of x and y's not y's x s because you have suppose x3 x1, x2, x3.Now, this x1 between minus 1 and plus 1 can also have a number of data points . So, now,this would choose from 3 to 5 those data points and will give you a recipe. Again you willcarry out experiments and it will try to fit the methodology or the technology is the sameit will fit the data in a model model. Now what kind of a model preferably a linear modelif you end up in a linear model what does it mean.It can work. Change the. What does it mean now you are working withoptimization what does it mean . It works with the optimization.That the range which you selected was not right . So, it has to be a converging pointnow we do not go beyond with an assumption you will generally see people do not go beyondquadratic and cubic nor no 4 factor or 4 degree polynomial or 5 degree polynomial why do youthink . If you have selected 4 4 factors from your suppose screening design which were crucialultimately the interaction can go up to 4 degrees there are a b c d isn't it, but whatis generally done only quadratic effects are taken into account means up to only 2 degreesbecause the effect it is not that on paper it is wrong, but the coefficient which isassociated with these now in a polynomial which is a 3 degree polynomial what all differentfactors you would have you can a quadratic equation.For example, you will have y is equals to can be m x m x square mx cube if there are2 factors can be m x1 x2 m x1 x2 x3 can be m x1 square x2 so on can be such a long polynomial, but generally the higher order terms are neglected because their coefficient associatedwill not be as significantly impacting your response. If so then one has to look intothe model equation. So, then thereafter once you fit and always use for analysis of variance.This will tell you that how is the fitting good or not the error once you did the experimentis acceptable or not. So, that is where your statistics comes intothe picture whether to what confidence level you can accept this model. If the confidencelevel is good the model is able to predict the confidence of the prediction by the modelis accepted . Now once you have the model now suppose now model is ready which meansnow values to the coefficients have been assigned in this polynomial equation this is a model.Now how do you use this equation to determine the optimum values . This is all this we weredoing to generate the model isn't it . Now coming on to our ultimate objective I needto . Now how this model is going to help you to optimize . Where your in silico approacheshelp. Manually it is difficult because it is a polynomial which means now this modelcan predict for different x1, x2, x3 it can predict a number of y's.Hm according to the response. So, now, in silico you can generate what aplot with a change in access how is y changing and if the objective function can be keptas put y maxima and solve this equation to give me the value of x1, x2 and x3 for y maxima. We can use a number of mathematical methods . Numerical methods are available isn't it.So, the this is what goes on in the background of these tools you generate contour plotsbecause these are converging. So, in a 3d surface which is called as response surfaceyou must have a seen surfaces coming out 3d surfaces. So, with the change in so generallywhen you see contours it will show you the effect of any 2 factors it is a 2 d plot.So, it will pick and choose. So, now, it is the user defined which 2 factors. Now howwould you define which 2 factors. You can go back to your screening design and see orin your model which factor coefficient was maximum. Suppose carbon and nitrogen werecoming and the top 2 rank. So, you would try to make a contour plot between carbon andnitrogen which is a 2d plot keeping rest of the factors are there average values and yousee how is your response changing and you keep generating these data points. So, insilico what it does is all these data points because this is a converging plot. So, arounda circumference whatever is the value of x1, x2, x3 will give you the same response.So, when you keep maximizing it will converge to a single point where your x1 and x2 willbe the value a single value which is giving you the maximum y value that is how it isdone . So, this is how you will get to the optimum value . Now in your when you willsee tools depending on the confidence of your model they sometimes differentiate the areasof because it is a 3d surface how will you get to know although I am getting a maximahere, but how do I know that how much is the confidence interval although I am gettinga maxima here, but my x1, x2 predicted here are falling in a lesser confidence value.So, then I would not pick that I would rather pick a lower response value where the confidenceinterval of the model is high. So, that is where you use these 3d surfaces and 3d surfacesthey have a colour demarcation through which you can the user can know where the modelhow is the model confidence varying in different regions of your design space ok. So, thatis how media optimization or any kind of optimization is done and is useful because in minimum numberof experiments you can get to the optima .
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