 As you know a screening for TAAs or tumor associated autoantibodies is a novel concept where the aim is to detect the autoantibodies or antibodies produced in the body much ahead of time. And they have lot of clinical utility especially for the early detection of cancer and other diseases. In today's lecture MS Nikita will discuss about a few more applications of protein microarrays using different case studies to provide you a broad understanding of potential of protein microarray based technology. You must understand and appreciate that there are many applications which are possible on different type of protein microarray based technology platforms. This lecture will also provide you understanding for novel applications for doing various protein interaction studies, post translation modification, kinase substrate screening etc. using high throughput microarray based platforms. So let us welcome Nikita for today's lecture. A very good morning to all of you. In the previous lecture you have seen how protein microarray can be used to detect the presence of autoantibodies in the bio fluids of cancer patients. In this lecture we will further look into the applications of protein microarrays that can be used to understand the signaling network and to understand the time bound post translation modification happening at the cellular level. Protein protein interaction occurs when two or more proteins interact with each other to carry out a biological function. These interactions mediate several cellular processes and understanding these interactions would help in understanding the function of proteins and to identify the disease pathobiology. So once we detect these interactions we can end up finding few drugable targets and new therapeutic approaches that can be used to treat the disease. Traditional approaches like yeast to hybrid system, tandem affinity chromatography etc. have provided invaluable insight into the protein protein interaction. However these techniques just look at one or two proteins, study these proteins in isolation and sometimes even end up giving false positive results. These networks the signaling pathways are dynamic therefore studying a protein in isolation might not provide a fuller picture of the interacting pathway. Therefore high throughput platforms like protein microarrays can hold immense value to screen multiple proteins together and hence can be used to decipher the protein-protein interactions. So let us start with one of the case studies where Chan et al have used protein microarrays to understand the pathway of T lymphocytes upon activation with CD3 and CD28 antibodies. Chan et al have made multiplexed reverse phase protein microarray and these protein microarrays were used to study the pathways in T cells which were activated upon stimulation with CD3 and CD28 molecules. In this current study they monitored the site specific phosphorylation of numerous signaling molecules and they performed a time bound experiment to look into the pathways that are activated upon stimulation with the cell receptors. So to check whether this reverse phase protein microarray is working, they first took the zurkat T cell lines and activated it with PMA, PMA is furball 12, myrosate acetate. This PMA activates protein kinase C, this protein kinase C once activated leads to phosphorylation of MAPK and MEK proteins and hence the phosphorylation was studied, the cell isates were taken and imprinted in triplicates for the untreated as well as PMA treated cell lines. The phosphorylation of these proteins were studied using phosphoantibodies. In this diagram you can see that MAPK showed a very good phosphorylation upon PMA treatment whereas the untreated cells did not show any phosphorylation, MEK also showed a differential phosphorylation upon PMA treatment whereas AKT which was not a target of protein kinase C showed no change in the phosphorylation levels. SLP76 and beta actin were used as control and no changes were seen in the treated as well as the untreated cells. The same was verified using western blot which is shown in this image. Once they were sure that this experiment is working they have taken the T zurkat cell lines and they have treated it with CD3 antibody, CD28 antibody or CD3 and CD28 antibody in combination. The cell lines were stimulated over the period of 30 minutes and the cell isates were imprinted at 6 different time points. The time points were 0 minutes, 2.5 minutes, 5 minutes, 10 minutes, 20 minutes and 30 minutes. These cell isates were then probed with phosphoantibodies to look for the phosphorylation status. Further these slides were incubated with HRP conjugated secondary antibodies. Amplification was further performed in which HRP catalyzes accumulation of biotinylated tyromide. This biotinylated tyromide was further detected using streptavidine which was labeled with Cy3. Simultaneously these arrays were also probed with Cy5 linked antibodies to detect the level of actin in the cell isates. Here in the array picture you can see the red spot shows the actin level whereas the green spots show the phosphorylation status of the cells. This is one of the sub array where the phosphorylation of map K was studied. The cells were treated with isotype antibodies which acted as control. The cells were treated with CD3 antibody, CD28 antibody and CD3 and CD28 antibody in combination. Here you can see that when the cells were treated with CD3 there was a quick phosphorylation observed at 2.5 minutes which reduced at 5 minutes but there was no change in the phosphorylation status of map K when the cells were treated with CD28 antibodies. When the cells were treated with the combination of CD3 and CD28 a sustained phosphorylated map K was observed and the signal intensity even at 5 minutes was prominent. Further to study the signal transduction kinetics the authors study the phosphorylation level of phosphorylated C gamma protein. In this again the cell lines were treated at different time points and cells were treated with isotype antibodies as control with CD3 antibody, CD28 antibody and a combination of CD3 and CD28 antibodies. Also the protein microarray was probed with non-phosso antibodies to study the overall concentration of phosphorylated C in the cell isate. The graph shown here shows the adjusted level of phosphorylated PLC gamma with the total phospholipase C present in the cell. So in this graph you can see the phosphorylation kinetics did not change when the cells were treated with isotype control antibodies. However when the cells were treated with anti CD3 antibodies a quick phosphorylation was seen at around 2.5 minutes which then dropped at 10 minutes and reached the baseline level. The green line shows the phosphorylation level of PLC upon treatment with CD28. Here you can see that although the phosphorylation was less but then it was sustained till 30 minutes. When the cell lines were treated with both CD3 and CD28 antibodies a quick increase in the phosphorylation status of PLC was seen at 2.5 minutes similar to CD3. However this phosphorylation sustained and reached the level which was similar to the level that was obtained upon activation with CD28. To further delineate the signaling path phase a cell line that is J gamma 1 which is a mutant cell line of Zorka T cells which do not have the phospholipase C was used and wild type T Zorka cells were seen to study the phosphorylation kinetics of the downstream signaling components. In this case J gamma 1 cell lines and the wild type cell lines were treated with CD3 and CD28 antibody in combination. Different time points were studied in the first graph you can see that the levels of phosphor PLC should have increased phosphorylation at around 5 minutes which gradually decreased. However there was no change in phosphorylation status seen in the J gamma 1 cell lines informing that these cell lines are deficient in PLC. Further the phosphorylation status of MAPK and MEK were studied and here we can see that in the wild type cell lines the phosphorylation of MAPK and MEK sustained over 30 minutes. However in case of mutant cell lines the phosphorylation dropped drastically upon 20 minutes stating that phosphorylation status of MAPK and MEK is dependent on the presence of phospholipase C gamma protein whereas when the phosphorylation status of AKT was seen no change in the phosphorylation status was seen in the wild type as well as in the mutant cell lines. This infers that the presence of phospholipase C does not affect the phosphorylation kinetics of AKT protein. To further understand the signaling events in the T cells Chan et al activated T Zorka cell lines with CD3 antibody and with CD3 and CD28 antibody in combination. These cell lysates were stimulated for 2.5 minutes and were imprinted in 6 replicates onto the nitrocellulose membrane coated slides. Further the phosphorylation status for these 62 proteins were studied using phosphoantibodies. In activation with CD3 13 proteins showed a substantial change in phosphorylation when the cells were stimulated using CD3 and CD28 14 proteins showed change in phosphorylation of which most of these proteins showed an overlap. In this study they identified that the RAF1 protein showed dephosphorylation upon stimulation with the antibodies. Further to study the phosphorylation kinetics of RAF protein and its downstream signaling pathway the cells were stimulated using different combinations of antibodies. Upon 2.5 minutes steep dephosphorylation of RAF protein was seen in cell lines treated with CD3 antibody and CD3 antibody in combination with CD28 antibodies. There was no change seen in the phosphorylation level of RAF protein when the cells were treated with CD28 antibody. Further they studied the phosphorylation patterns of MEK and MAPK proteins. This phosphorylation pattern matched well with the dephosphorylation patterns of RAF protein and as the RAF protein dephosphorylated increased phosphorylation of MEK and MAPK was seen at 2.5 minutes which substantially degraded over the period of 30 minutes. And the cells treated with CD3 antibodies and the cells treated with CD3 and CD28 antibodies in combination. This dephosphorylation of RAF was further cross checked using western blot. To conclude Chan et al studied time dependent phosphorylation kinetics of several downstream signaling molecules in a time dependent manner. They concluded that PLC gamma 1 is not essential for the ERK kinase pathway as there was no change seen in the phosphorylation of AKT in the cells that were deficient in phospholipase C protein. Also they screened the phosphorylation level of 62 downstream signaling proteins and identified a novel instance where RAF 1 showed dephosphorylation upon T cell receptor stimulation. Now going ahead to the another study where raw et al prepared an acetylone peptide microarray to screen the activity of 7 different isoforms of certuence against 6800 unique mammalian acetylation sites. Certuence are the enzymes which deacetylate the lysine residues in the presence of NAD. In this study database search was performed to look for all the conserved acetylation sites in the mammalian system a total of 6802 peptides in its acetylated and nonacetylated forms were imprinted. The peptides that we used here had lysine at the 7th position which was flanked by 6 amino acids at the upstream as well as at the downstream. So therefore a 13 mer peptides were imprinted onto the arrays and the total of 13604 peptides were immobilized in triplicates. These peptide arrays were further incubated with different isoforms of certuence and without certuence and they were also incubated with and without NAD to check for the activity of certuence. These peptide arrays were further probed with primary and secondary antibody to look for the change in the level of acetylation upon incubation with certuence. The decrease in the signal intensity of acetylation was further calculated using Welch T-Test. These acetylation patterns were also validated using mass spectrometry and this study resulted in identification of substrate preferences for different certuence isoforms. Further, this study ended up in identification of new targets for certuence. So first in this study what they have done is they have printed an array, SA represents sub array. These sub arrays were treated with buffer control where no certuence were used. These arrays were also treated with certuence with and without NAD. Since certuence need NAD for their activity, there shall be no deacetylation seen when there is no NAD present. Here you can see that there was no change in signal in buffer control as well as when the array was treated with certuence without NAD whereas a loss in signal intensity was seen when the arrays were treated with certuence in presence of NAD concluding that certuence need NAD for deacetylation and also confirming that deacetylation is happening on the array. This graph represents the specific activity of certuence 3, how the deacetylation is happening for different peptides. The last protein that is AATaseK was used as a negative control and has shown no change in the deacetylation pattern. This heat map shows the deacetylation activity of all the 7 isoforms of certuence across 6800 peptides. Certuence 1, 6 and 7 locates at the nucleus however when you look at the target peptides there is a specific pattern of preference of these peptides for certuence 6, 7 and 1. If you look properly at certuence 6 and certuence 7, a specific deacetylation pattern is seen which signifies that these two isoforms has their specific targets whereas certuence 1 shows a nominal activity across a wide range of substrate in the nucleus. This logo here shows the peptide that we used. The upper panel of the logo that is the enriched section shows the preferred amino acids for each certuence whereas the lower bottom shows depleted amino acid sequence that is these sequence that do not favor the deacetylation. Also the right panel shows the peptide binding grooves of these certuence molecules whereas the blue region signifies the positively charged amino acids and the red region shows the negatively charged amino acids. The peptide preference for certuence 1 is majorly positively charged amino acids that is arginine or lysines as the core has negative charge therefore certuence 1 prefers the peptides that have positive charge specifically at position minus 5, minus 1, 1 and 4 whereas the peptide binding group of certuence 6 is majorly hydrophobic and hence the peptide sequence that are specific to certuence 6 majorly have hydrophobic residue specifically at minus 1, minus 2, plus 3 and plus 4 sides. However at plus 2 and minus 4 there is a negatively charged residue. Coming to the other isoforms of certuence that is 3, 4 and 5 which locates at the mitochondria. Here also you can see that there is a huge change in the preferences of the peptides that are selected by all the 3 different isoforms. In this you can see that the peptide binding groove for certuence 3 is highly negative owing to that the peptides that are preferred by certuence 3 had a lot of positively charged residue specifically arginine at the upstream of the acetylated lysine. For cert 5 you can see that at position 1, choline was predominantly present, the other upstream amino acids were either positively charged or non-polar whereas the downstream amino acids were majorly positively charged. Coming to the another certuin that is cert 2 which is majorly found in the cytosolic region of the cell you can see that the peptide binding groove for certuin 2 is highly negative and therefore it disfavors the presence of negatively charged amino acids in the sequence preference. Except for certuin 4 all other certuence have some or the other targets for deacetylation. However there was no identified substrate for certuin 4. In the flourishing essay certuin 4 showed a low but consistent deacetylation activity upon incubation with NAD. From this study NADP transhydrogenase stress 70 protein was found to be one of the substrate specific for certuin 4. To confirm this deacetylation activity of certuin 4 the deacetylation of NADP transhydrogenase stress 70 protein was performed using wild type certuin without NAD, wild type certuin with NAD and a mutant certuin which did not have the deacetylase activity. When the substrate was incubated with wild type certuin 4 and with NAD a strong deacetylation activity was seen confirming that NADP transhydrogenase stress 70 protein is a substrate for certuin 4. To conclude this study has used microarray platform to parallely screen around 6000 peptides for 7 different isoforms of certuin. Using this platform the authors were able to identify the sequence specificity for different isoforms of certuence. They also identified a substrate for certuin 4 which is NADP transhydrogenase stress 70 protein further they confirm that Mali dehydrogenase protein is one of the target of certuin 3 and peroxyredoxin 1, peroxyredoxin 3 and mitochondrial protein HSP60 are targets for certuin 5. This peptide microarray platform concluded that all these different 7 isoforms of human certuence have a sequence specificity and preferred substrate for deacetylation. To conclude protein microarrays holds immense potential in identifying new targets in delineating the pathway and hence providing a deeper insight into the signaling kinetics at cellular level. Thank you. I hope by now you understood that there are wide applications of protein microarray could be achieved especially from different type of protein microarray based technology platforms in the areas of detection for novel protein interactions post transition modification in high throughput manner. These examples would have also provided you an insight into the utility of protein microarray based technologies for screening several proteins in parallel providing a holistic understanding of the post transition modification and signaling networks. In the next lecture we will talk about how to make arrays and print your own chip using novel printing technologies. So I will see you next lecture and we will talk to you about the latest advancement in this area and how you can make your own arrays and recent developments in the areas of printing technologies. Thank you.