Science topic

Gene Regulation - Science topic

Regulation of gene expression (or gene regulation) includes the processes that cells and viruses use to regulate the way that the information in genes is turned into gene products. Although a functional gene product can be an RNA, the majority of known mechanisms regulate protein coding genes. Any step of the gene's expression may be modulated, from DNA-RNA transcription to the post-translational modification of a protein.
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A patient with desminopathy survived Covid-19 six months ago without pneumonia, but with a temporary loss of smell and taste. After Covid-19, we note an accelerated progression of desminopathy, penetration accelerates, new muscles are quickly involved in the pathological process, muscle mass decreases, and heart function worsens. Perhaps the infection or its consequences are somehow connected with the mechanism of progression of desminopathy?
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To save life in desminopathy, can the body purposefully reduce muscle mass, for example, due to decreased heart function or for another reason?
It is known that when hypothermia, the body sacrifices limbs for survival. Is it possible with desminopathy a similar phenomenon?
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Dear Mozhgan Norouzi, thank you very much for your reply!
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Hi, Iinserted gene of Reverse transcriptase into pPLc245 plazmid. If I'm right, this plazmid doesn't code cI857 represor. For expression od reverse transcriptase from this plasmid I used E. coli DH10B. RT was expressed after increase of cultivation temperature to 37 °C. Before this thermo induction I cultivated E. coli DH10B with pPLc245 at 28 °C. But at this temperature RT was not expressed. Why is this possible? Is E. coli DH10B coding cI represor or pPLc245 could contain gene for this represor?
Thank you for all responses.
Bohuš
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If your plasmid really is pPLc245 (and not some derivative of it) then it should not carry the lambda repressor gene and you should get constitutive expression at any temperature. So I can't really explain your result unless RT does not fold properly to have activity at RT or 28.
I'm actually a bit surprised this worked at all for you though, generally plasmids with superstrong promoters like lambda pL are not very stable under conditions where there is no repressor.
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Hi all,
I want to know the kinetics of a transcriptomic response to infection. I am interested in the earliest time points, how minutes does it take a cell to activate a gene upon infection?
Thank you for your insights
Julien
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The cascade leading to the transcriptional factor activation is short, in the case of the canonical ones (NFkB, IMD). The accumulation of the transcripts is another subject matter. The structure of the promoters of AMPs suggest non immune related transcription factors are likely to bind and interfere with the specific transcription. HIF binding site, for instance, is frequently found nearby these genes, suggesting a potential hindrance upon redox stress.
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I am looking for a "not too old" review or paper on the regulation of NR or in general denitrification in bacteria. In particular I like to find an answer on how nitrite accumulation could inhibit nitrate turn over.
Thanks!
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Frontiers | Transcriptional and Post-transcriptional Control of the Nitrate Respiration in Bacteria | Molecular Biosciences (frontiersin.org)
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I need to identify and compare TFBSs in a number of sequences. I've used Transfac with the Match program (http://gene-regulation.com/) before but it seems that the website has been having issues lately. Are there other programs that can accomplish similar tasks? Ideally I'm looking for something browser based, but I can work with command line if that's the next best thing.
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Dear Jacob
Kindly read following review article in which they mentioned few online tools other than TRANSFAC
Best regards
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I am using DAVID (https://david.ncifcrf.gov/home.jsp) to cluster some genes I found upregulated in my RNAseq data. I am just using the official gene symbol without any quantitative data. However, the KEGG pathway results are giving me p-values which are extremely high. It does not make any sense to me. How the p-value can be calculated without any number? Can the p-value be significant?
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DAVID adopts Fisher's Exact test to measure the gene-enrichment in annotation terms. It is just a matter of making a 2x2 contingency table, as in the example here: https://david.ncifcrf.gov/content.jsp?file=functional_annotation.html (section 2.2).
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A Hypothetical Example In the human genome background (30,000 genes total; Population Total (PT)), 40 genes are involved in the p53 signaling pathway (Population Hits (PH)). A given gene list has found that three genes (List Hits (LH)) out of 300 total genes in the list (List Total (LT)) belong to the p53 signaling pathway. Then we ask if 3/300 is more than a random chance compared to the human background of 40/30000. A 2 x 2 contingency table is built based on the above numbers: List Hits (LH) = 3 List Total (LT) = 300 Population Hits (PH) = 40 Population Total (PT) = 30,000
Exact p-value = 0.007. Since p-value < 0.05, this user's gene list is specifically associated (enriched) in the p53 signaling pathway by more than random chance.
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Hence, quantitative data are not considered in such enrichment analyses unless you don't want to calculate an additional activation/inhibition score, as computed by Ingenuity Pathway Analysis, for example.
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I'm trying to purify a natively expressed protein from a large operon, native expression levels are very low, does anyone have any experience with changing the innate promoter with let's say an inducible one? Is it possible? I'm trying to find any literature on that, but don't see much.
I'd appreciate any help :)
(heterologous expression from a vector is not an option)
All the best!
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alright then you can use lamda red to take the regulatory region of a plasmid for induction and recombine it instead of the native promoter. You can for example use pQE-5 as template (https://www.snapgene.com/resources/plasmid-files/?set=qiagen_vectors&plasmid=pQE-5) you add homology arms that are 50bp start from the atg codon from your target locus and extend 50bp and do the same with the other homology arm (I cannot advice where to stop since I do not know the locus you are targeting therefore you will have to use your own judgement for that). The pQE-5 plasmid has an IPTG regulated t5 promoter hence no need for a t7 strain and it also has an amp maker close to the promoter add your homology to this fragment allows to easily identify the recombinants that took up the promoter + amp (hence the wt promoter has been switched). Of course you can use whatever plasmid you want as template depending on the system you want to incorporate just make sure you gel purify your fragment before electroporation otherwise you will end you with the plasmid itself rather than the promoter swapped region.
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We have prepared a list of genes regulating the shoot branching and some of them are newly mapped by us. Now, I want to prepare the list in the graphical visualization by mentioning the number of all genes, the number of newly mapped genes, their genetic+physiological positions, and their components e.g. phytohormones/ transcription factor/cell organization etc.
Suggestions and guidance will be highly appriciated.
Thankyou!
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Maybe a network of interacting genes. (It is similar described in the diagram, but maybe you would like to include it all in one? You may try R language with some packages. Or maybe more specifically for plants. Could there be a "blast" for plants in a database? Or maybe a specific program for plants?
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Is there any database that can provide me with information on how a particular gene is regulated (for example, names of transcription factors)
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awo! great, thanks
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I Interested in to work in gene network modeling thus I need to know what is future of gene network modeling in agriculture
thanks
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interested
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I have analysed some bioinformatically important information relevant to gene regulation. I want to publish it.
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Hi,
Pharmacognosy Magazine, Bioinformation, Advances in Bioinformatics, Current Drug Discovery Technologies, Chemistry Research Journal, In silico Pharmacology, Medical Hypotheses, Journal of Biomolecular Structure and Dynamics.
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I would like to create a biosensor in which gene1 produces the cellular receptors for a ligand. Upon the binding of this ligand I would like the transcription of gene2 to be activated. This can be done with a histidine kinase receptor.
Mostly, I want to know if this can be done with 1 vector and not 2. If yes, then how can I promote the expression of gene1 under all conditions and not the gene2.
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Great! Hope you figured out how to get one induce the other. Good luck.
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Anybody has a good recipe for homemade SYBR green mix for real time PCR?
To my understanding, one of the key factors is the taq enzyme because most enzymes are inhibited by the SYBR dye.
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Is the recipe by Mark working? Please share the experience. Note section is little confusing. Can you please elaborate it @Mark
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Hi,
I am working on molecular validation of co-expressed genes in Rice under moisture stress.
I have a list of genes that are co-expressed in three rice varieties, under a particular set of physiological conditions. How do I plot/draw a gene regulation network ?
What else data do I need to do the same? Is there a Bioinformatics tool?
Thank you
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We recently identified a novel transcriptional isoform of a gene in brain. It's endogenous expression is very low compared to the annotated one. Exon 1 of the gene is missing, and a portion of a long terminal repeat (33bp) spliced into Exon 2. Thus, the first ATG for this new isoform is found in Exon 6 due to the loss of Exon 1. my question is: 1. is the new isoform translated into protein? 2. if not, how can we test it is a non-coding RNA? 3. If it is translated, how can we test the protein it makes.
Thank you very much!
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northern blot analysis
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Hi everyone,
With the weird social isolation issues we are all facing i am hoping to find a few people to start some discussions.
If we can't attend conferences, then why not try some other means of trading some knowledge to help get our experiments moving again when we are back in the lab (if you find yourself in isolation that is).
I have a project at the moment looking at epithelial mesenchymal transition in CF airways. I am a little bit stuck at the moment after developing a lineage tracing vector, which possibly stems from not enough fore thought regarding E and N-Cadherin gene regulation.
If anyone has any experience with EMT, E or N-Cadherin gene regulation, or lineage tracing vectors/methods, it would be great to chat to you.
Happy to discuss via email and or zoom
Kind regards,
Nathan
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Legitemedly, sure it would not be expressed, because as you knock-out the first exon probably by frameshift, all you get is residual of proteins which are not functional and decays swift. Sometimes, however, there are secondary starting codons in different part of exons which can produce sort of pseudogenes but rearly functional.
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I am looking for putative transcription factors binding sites (which I know the sequences of) on some promoters (which I also know the sequences). What I want is a software where I can upload my promoter, the consensus sequence of one TF, and it tells me how many of putative binding sites (with a certain degree of liberty) can be found on my promoter sequence.
(FYI, I work with budding yeast)
Thanks for you help
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Nice Topic , Following
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I am sure if the binding site of a microRNA can be implicated on a gene or mRNA there one can conclude about the mechanism of action and in a cancer case, its parthenogenesis.
Is the binding on both 3' and 5' end of mRNA, just 3' UTR or other coding region?
Recall also that they have multiple targets, if this microRNA binds to more than one sites, can can one implicate the specific one responsible for regulation?
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Good Answer Satyajeet Salunkhe
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Suppose i have a DNA sequence and i want to find transcription strat site, CDS, poly A signal etc., which software will be useful to find this out?
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#GlimmerHMM is a new gene finder based on a Generalized Hidden Markov Model (GHMM). It actually helps you to annotate the draft genome by running a few simple commands.
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The attached image shows chromatograms from the same FAME sample run three times on our GC-MS. As seen, additional peaks show up if running the sample several times. From the MS spectra the additional peaks seem to be plasticizers. If I heat the column to max for 30 min and then rerun the sample the peaks are gone. The additional peaks elute at approximately the same in all samples. I have tried changing septum, liner, injector needle, needle wash whiteout any improvements. Any suggestion how to lose these peaks? Thanks in advance.
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What is m/z for plasticizers peaks?
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Hi all,
I am working on the interaction between C. elegans and the nematode-trapping fungus. Now I found a gene in C .elegans called epc-1 which will have the phenotype I want when it was deleted. It is to contribute to histone acetyltransferase activity. Now I am wondering how to find the genes regulated by it.
Could anyone give me some suggestions? I will very much appreciate it.
Thanks,
HanWen
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Hi Hanwen,
There are a number of websites that compile gene information, but the biggest determinant for you in choosing a website is probably the one with the most relevant and detailed information for your organism. Some general websites include Uniprot and NCBI.
If you have a set of genes that you want to identify pathways, GO-term searches can be helpful and can be acquired from websites like http://amigo.geneontology.org/amigo.
In the end, I think the best source of information would be searching the primary literature or reviews that cover your gene of interest. You can find literature in Web of Science, Pubmed, or even Google Scholar.
If your gene has never been studied before, there still are ways to get some hypotheses on relevant pathways, namely to search for sequence homologues of your gene in other organisms where there may be more information (websites such as BLAST or https://www.flyrnai.org/cgi-bin/DRSC_orthologs.pl).
Thanks,
Barry
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I have got a promoter region which is size about 1000bp from human genome. I'm trying to find cis acting elements corresponds for gene regulation in multiple myeloma. What are the freely available methods for this?
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In brief,
1. Use the genomic sequence to find out potential transcription factor binding site(s) using the TRANSFAC program (or any other free program);
2. Generate a reporter construct with the promoter sequence to be tested;
3. Use potential sequence(s) for a candidate TF to perform binding assays using the labelled cis-sequence;
4. Mutate the potential TF binding site(s) in the reporter to demonstrate the specificity of binding;
5. Perform ChIP assays to demonstrate binding of a TF to cis-sequence in vivo (in cells).
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I'd like to purchase some custom DNA microarrays, circa 100K spot density and 30mers in length. Would anyone be able to recommend a company?
thanks
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You can visit this website http://www.sciomics.de/services/microarray-printing. Hope this helps
Regards
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In a patient with hereditary desminopathy (Thr341Pro DES mutation in the heterozygous state), a significant loss of muscle mass is observed after a night's sleep, with its replacement by adipose tissue. How to reduce muscle loss during sleep?
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Dear Ali Javadmanesh, Adrian Fierl, Abdulnabi Abdullamer Matruod, thank you very much for your answers!
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Hi,
i am currently looking for an experiment alternative to southern blot. I heard that pcr based assays give results quickly ( let's say within few hours). I want to perform sybr green relied pcr to detect copy number of my interested gene in the human genome like in southern blot. however, I couldn't find a proper protocol. If you address a protocol or share your experience, I will appreciate.
Thanks.
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Agree with the author above. If there are multiple copies of GOI scattered around genome, Southern blot may not resolve all of them, and qPCR may also be inconclusive. You may need to do NGS using long read platform to convulsively determine the copy number. qPCR is handy for an estimate.
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I need a suggession for a good RNA isolation protocol from Serum/Plasma. Looking for any kit name of any modification of protocol etc
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Hi Andrea,
RNA found in both plasma and serum is normally fragmented RNA or small RNA , mainly miRNA, and is either bound to proteins or contained inside extracellular vesicles. If your target is to purify mRNA from plasma/serum then you have to be aware that this mRNA may not be the full length, original RNA, that you may be getting when isolating RNA from whole blood.
I personally recommend for you using one of Norgen's Plasma/Serum RNA Purification kits ( https://norgenbiotek.com/sites/default/files/resources/Plasma-Serum-RNA-Purification-Kit-PI55000-5.pdf). These kits covers a sample volume range from 50ul up to 5mL without using any phenol or carrier RNA. Unlike other purification kits, Norgen's kits uses Silicon carbide as its separating matrix instead of silica. Some literature has mentioned that silica-based technology with/without phenol has a bias towards binding large RNA sizes as well as a bias towards binding RNA with sequences containing high GC contents whereas Norgen's Silicon carbide doesn't have such a bias.
For the isolation of RNA from blood, this should be a straight forward isolation but you have to use a different isolation method for this. I also recommend using Norgen's Total RNA Purificiation kit (Cat. 17200) for this.
When isolating RNA from plasma/serum you should be expecting low RNA amounts (normally in the picogram range) therefore you can't quantify you plasma/serum RNA using conventional methods such as regular spectrometer or Nanodrop since they are not sensitive enough to quantify such low RNA amounts. I recommend using Agilent Bioanalyzer RNA Pico Chip for quantifying plasma/serum RNA. Also don't relay on the RIN values from the bioanalyzer chips cause it will be low and won;t reflect the quality of the purified RNA. RIN values are calculated based on the ratio of the 28S rRNA and the 18S rRNA and since plasma/serum doesn't have cells therefore the purified RNA won't have these two bands which will lead to a very low RIN value. The best way to evaluate the quality of the purified RNA is to amplify a highly abundant small RNA target such as the 5s rRNA or to amplify a highly abundant miRNA such as miR-21. I believe that what Norgen does when performing small RNA sequencing services. https://norgenbiotek.com/services/small-rna-and-microrna-next-gen-sequencing
Sorry for the long message but I just want to give you some detailed information so you don't face any issues through out you project.
I hope this answered all of your concerns.
Best Regards and Good luck.
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I want to check whether any response element is present for a particular set of transcription factors on my gene of interest. I have already found EPD (http://epd.epfl.ch/) for promoter sequence and motif search and JASPAR (http://jaspar.genereg.net/) for response sequences. But the problem is, I am not able to merge those information.
The problem with EPD is, many gene promoters are not available. Even if they are available and I find transcription factor motifs on my gene of interest, there is no way to see them as sequence and annotate it.
So, if someone knows any software/ database/ technique for this purpose, it will be immensely helpful for me.
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Biswajit Biswas I'd also recommend looking at the various ENCODE tracks. For example: https://genome.ucsc.edu/cgi-bin/hgTrackUi?hgsid=725021383_RGLKNnOIuYWhC8gnLaWXEWCGidL3&c=chr21&g=wgEncodeTfBindingSuper gives you actual TFBS data from experiments. You can click on the names of any track to see detailed information. Keep clicking through the links on the subsequent pages to turn on/off specific TFs and cell lines.
For mouse, there are several experimental TFBS tracks in the mm9 assembly under "Expression and Regulation".
As Frederic Lepretre pointed out, the table browser option will allow you to pull the associated information for your genes/regions of interest. I'd also be happy to help further by private message, if you need it.
Good luck,
Ryan
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Predicted G2-M phase cell cycle defect mutant change ploidy distribution , but most of the cell cycle progression gene up-regulate in mutant background.
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Thank you, Mr. Nashaat Ghalib, for your interest. I found the opposite expression pattern of some important downstream gene.
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There are specific gene for specific expression. But if any one gene regulated ( up or down ) then other gene will also effected for their regulation or not?Though they may or may not be interlinked.
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Thank you for your suggestion.
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I have very limited resources in my lab and very narrow budget. I used to use the red blood lysis solution, but I'm now trying to find a new protocol. Can anyone help?
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How I can isolate WBC from whole blood ?
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When we have a positive regulation the control is tight, so we have low background expression under non-induced conditions.
Negative regulation can not be fully controlled, but as far as I understand it is more popular than positive regulation.
Why?
Are there any other important features of these two types of regulations?
Thank you in advance!
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I think many of the respondents are mixing up the difference between positive and negative regulation, which is defined as the behavior of the regulatory protein, which is not the same as a inducible or co-repressible system. For example in E. coli both the arabinose operon and the lactose operon are inducible by the sugar, but lac operon is primarily controlled by a repressor and hence negative regulation whereas ara operon is positively regulated by a transcriptional activator (I realize that is an oversimplification for both but primarily correct).
For controlling gene expression and inducible system is normally easier to regulate because you just need to add the small molecule inducer to turn on gene expression, whereas in a co-repressible system you would need to remove the co-repressor (frequently an amino acid or something similar). So from that context inducible is much easier.
Whereas the difference between a negatively regulated vs a positively regulated system is about the behavior of the regulatory protein. The problem with a negatively regulated system is that for controlling a multi copy plasmid you need to have excess repressor present, and usually a single copy of the repressor gene on the chromosome does not suffice. So often negatively regulated promoters are not as tightly regulated and may have substantial basal expression. Whereas for positive regulation you don't have the same difficulty and the basal uninduced expression levels are usually lower (more tightly regulated).
As to why negative regulation is more common in plasmid systems, I think it primarily is historical. The lac operon was extremely well studied and understood in E. coli at the time many cloning and expression plasmids were being developed and it has just stayed with us.
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To assess whether expression of the gene of our interest is associated with mutant status of p53 we have treated FaDu cells( mut-p53) with CP-31398, a Known p53 stabilizer, that restore a wild-type DNA-binding conformation of mutant p53. we check the expression by TaqMan based q-PCR, and got expected result, but when we treated the Fadu cells with Pifithrin-α( an inhibitor of p53 ) we again got the same trend( in both cases RQ is 0.2 & 0.4 respectively), while we are expecting No change or Induction. According to the publication: Cancer Biol Ther. 2002 Jan-Feb;1(1):47-55, FaDu expressed only 50% of the normal level of p53 mRNA, either because only one allele was present (A431), or because only one of the two alleles was transcribed. What could be the possible reason of same trend of gene expression after the exposure of CP-31398 & Pifithrin-α in Fadu Cells?
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May the the molecule of your interest which you are working is simply not involved in cascade. The result can be interpreted as it has no role in particular pathway or may be any other signaling deivn the proces. Thanks
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Dear all,
I am eager to know your opinions about site-specific expression of secondary metabolite genes in plants. Which one is more involved: epigenetic regulation, transcription factor-mediated gene regulation or post-transcriptional gene regulations?
P.S: It is clear that all mentioned items (and other mechanisms) are involved, but my question is which one is more engaged, specifically for secondary metabolite differential biosynthesis?
Many thanks for all your consultations,
Ahmad
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I'm trying to look at the induction of candidate genes involved in plant defence when I block the signalling pathways related to JAs and ethylene and apply different stresses. For ethylene I can use the AVG, an inhibitor of ethylene biosynthesis, but as far as I know, there are no inhibitors of the jasmonate signaling pathway. Do you have any info about it?
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I need to find an over-expressed thyroid hormone receptors hepatic cell line 
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good question
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Dear all,
Recently I am performing RT-PCRs and Western blots of a mammalian cell line in which I overexpressed two vectors (wild-type and mutated) of equal promoter and sequence length. However, in both RT-PCR and Western blot I observed very different expression levels between both vectors, despite always transfecting the cells with the same amount of DNA. Could these results be acceptable for publication? Could I assume that the mutation is affecting the gene regulation of its vector in a different way? Or should I normalize this effect in some way in order to explore changes caused in other genes/proteins?
Thank you
Jaime
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Hi there,
First of all you have to repeat the experiment in order to be able to validate the hypothesis that mutation has a significant effect at RNA/protein levels. If you want to normalize the data you definitely need an internal control (from a housekeeping gene both for RNA and protein levels).
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When I give a list of genes regulated by my protein of interest as input in GSEA MSigDB, does the output of C3 TFT mean that my set of genes regulate these Transcription factors?
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If I may complete the previous answers: GSEA calculate enrichment of a set of genes over the entire genome. If you get hits in C3 TFT, it means that your set of genes are probable targets of the transcription factors that are indicated by GSEA. Therefore if what you call "hits" are the C3 TFT results, it's understandable that they are not (all) in your gene subset. However, if you look at the genes which make the C3 TFT result significant, they should all be a subset of your gene list. Now, if your set of genes is regulated by a protein of interest and you get indication of putative regulation by some TF, it might be that your protein of interest is another TF working in dimer or a transcriptional cofactor and it may be worth investigating.
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Dr. Magnus Nordborg recently pointed out in a presentation that is no evidence that methylation is involved in either development or adaptation and there is still little evidence of the involvement with gene regulation.
Also, the paper "Epigenomic Diversity in a Global Collection of Arabidopsis thaliana Accessions" (Kawakatsu et al. 2016) showed methylation in Arabidopsis strongly correlated with geography and climate of origin.
It seems that environment controls both methylation and gene expression but there is not necessarily a cause-effect relationship between these two.
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I support the comments of MR Schaefer and I can contribute that epigenetic changes also interfere in the behavior of transgenic plants in field conditions.
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Gene regulation and environment are quite related with each other thats why the circadian rhythm is maintained but what are the exact factor for that specific gene expression and the molecular mechanism behind detecting the environmental changes by the human body?
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Ok sir.
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We are using lipofectamine for transfecting synthetic miRNA mimics for the miRNA functional analyses and miRNA target site validation experiments that we are developing with human cancer cell lines. However I would like to know if in your experience those experiments work as well with jet-PEY or similar reagents, which seems to be more cost effective. Thank you, Inma
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It all depends on the cell line, and the transfection reagent for it as well. Given the similarities between miRNA and siRNA, if you find reagents that work well for siRNA delivery it's likely they'll work for miRNA delivery as well. See this catalog (https://altogen.com/products-index/) and you'll see that different cell lines have different efficiencies, even for optimized reagents. Generics will work, but they won't be stellar. Look through previous studies to see what reagents they used for given cell lines, and you should be set for getting the empirical values for efficiency as well.
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We will performed ChIp and reporter gene assays to functional validate rSNPs identified within breast cancer-relevant regulatory regions. Which breast cancer line is most suitable for this study? or alternatively, how to select it among the available breast cancer lines such as MCF10 MCF7 HCC1954.
Thank you
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Dear Laura,
You don't give details about which association with breast cancer you are talking about but I assume it is association with risk (not outcomes) of breast cancer.
In this case (examining risk), the assumption is that this candidate SNPs would have its effects driving risk in a "normal cell" (the cell of origin of the tumor being studied) and therefore your best bet is to use a immortalized 'normal' MCF10A.
Sometimes 'normal' cells are not available or suffer from technical limitations (low transfection efficiency, or clumping during FACS analysis, for example). In this case, you could resort to cancer cell lines - understanding this is the 'next best model'.
If you decide to use cancer cells make sure you try to use a line that is representative of the tumor subtype associated with the SNP. Sometimes, a SNP is associated with risk of ER-negative breast cancer only and it would not be wise to use MCF7 or other ER-positive cell lines. You should be able to justify your choice of cell lines in light of the question you are asking.
Good luck,
alvaro
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Regulation of gene expression operates at different levels. If you are working on laboratory animals which have a problem with accumulation of a certain protein earlier than the stage when the organisms need it, how would you apply the concept of gene regulation to them? Assume that you have maximal power, capability and all the equipment needed.
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This is a very imprecise question. Is this specific for a strain of animals? Is it genetic and heritable? Does it cause a phenotype that is deterimental to fitness? Lot of genes are expresed in cells that may be superficial or unnecessary, but if they cause no harm then the cell has no reason to suppress expression. When you say earlier, do you mean in embryonic development? If so then the cells are likley to see a signal prematurely. They may have increased sensitivity to a peptide or morphogen, perhaps due to a variant in the receptor. Or, they may be missing a repressor that acts to inhibit expression early but is then switched off later. There are many models for how this could happen.
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methylation is un important process for gene regulation.
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Methylation is a very location-specific mechanism for gene repression, such that hyper-methylation of the gene promoter is primarily linked to reduced transcriptional activity.
In the context of adolescent diseases, imprinting disorders such as Angelman and Prader-Willi syndromes are classical examples of abberent imprinting disorders:
If interested in somatic diseases associated with DNA hypermethylation, the above mention of cancer is a great example. Specifically for adolescents, osteosarcoma and various leukemias (e.g. Acute Myelogenous Leukemia, AML) are malignancies affective younger adults:
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Nuclear extraction of bean tissue
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Hello guys, '
Is it a must to add PMSF ? I only have protease/phosphates inhibitor cocktail ?
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Many articles have used cloning method for understanding gene regulation. what other methods can be used to know the expression of common promotor in different gene regulation.
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You can insert a fragment of your promoter of interest in some plasmid, (for example, pGL3 Basic Vector) conjugated to a luciferase gene (reporter gene). Then you could create mutations in that recombinant plasmid to evaluate how the function of the promoter is affected. I did a similar approach using pGL3 Basic Vector from promega and I created different mutations using Q5® Site-Directed Mutagenesis Kit from NEB. At the end, you can evaluate the response of luciferase gene using the appropriate equipment. However, you need to consider the type of cells that you will use, the reporter plasmid and the length of the promoter that you want to evaluate.
I hope this helps.
Frances M
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I would like to prepare in silico analysis of role chosen by me transcriptor factor(TF) in the regulation few human gene expression.
Earlier I used the TRED: a Transcriptional Regulatory Element Database to the prediction present of transcriptional regulatory elements (TRE) specific for analyzed transcriptor factor(TF) in the promoters of analyzed genes.
TRED: a Transcriptional Regulatory Element Database (http://rulai.cshl.edu/TRED) was designed as a resource for functional studies and gene regulation studies.
Can you suggest me the free simple online tools to predict the presence of a transcriptional regulatory element (TRE) in the promotor of interested genes?
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Thank you all for your answer!
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I have read contradictory reports.
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Has it really been 5 years since I posted this question? How time flies! I no longer work in this field but thank you anyway.
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Gene regulation network of rice with respect to soil salinity and drought are used by researchers to study the genes and their interplay as these stress conditions lead to reduced production of crop produce.
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PFA
The attached content shall be useful to you.
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Enhancers and target promoters are often found "in contact". Some 'in contact' enhancer-promoter pairs stay dormant, i.e., there is little detectable promoter-driven transcription. But other enhancer-promoter pairs 'in contact' are 'active'. That is, both the enhancer and promoter 'in contact' are actively transcribing, generating eRNAs at the enhancers and mRNAs from the promoter. So, if we look at the 'in contact' enhancer-promoter pairs, they can either both be transcribing, or both not transcribing. My question is, is there any enhancer 'in contact' with a transcribing promoter but is itself not transcribing? That is, only the promoter is active, but the enhancer is not, despite both being in contact with each other? Shall appreciate any insightful answer that provides evidence, e.g., comparative 3C/HiC-RNA-seq data from same cell populations.
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Hi Anil,
Indeed, there may be eRNAs at the enhancer of FT that we overlooked so I cannot guarantee their absence. Several non-coding RNAs, smRNAs, and mRNA datasets did not reveal them though. About the contact of the enhancer with the promoter at the FT locus, there are two papers published (including one from my previous group): Cao et al., 2014 (doi/10.1105/tpc.113.120352) and Liu et al., 2014 (DOI: 10.1038/ncomms5558). In these papers, interactions within the FT locus were investigated using 3C (chromosome conformation capture). Unfortunately, the interactions between the promoter of FT and its upstream region are discordant between the 2 studies. Several factors can explain this discrepancy, including the fact that relatively short distances were probed (less than 5 kb). At the end, I would be really carefull when interpreting 3C data since this method is really tricky (see Jamge et al., 2017, doi.org/10.1186/s13007-017-0251-x).
About other enhancers at FT locus, yes, there are others, but you will have to wait a bit more for our next paper to get out ;)
What do you mean by mutualism exactly?
To get more information about enhancers in plants, I refer you to our review (Weber et al., 2016, doi: 10.1016/j.tplants.2016.07.013).
Best regards,
Johan
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Hello everyone,
Does anyone know which gene regulate the MyD88 gene expression in the intestinal epithelial cells ? or whether PI3K/AKT regulate the MyD88 expression or not? if MyD88 downregulated in your model, how will you check the signal pathway? Thanks!
Xin
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Hi Xin
Actually, you can use the following databases :
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I have a bunch of differentially expressed genes and a long intergenic non-coding RNA, what can do (bioinformatically first) to check the hypothesis that some of these genes may be directly regulated by this linc-RNA?
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Try to see the correlation between the gene expression and the lnc RNA expressions, as a preliminary analysis by writing a simple R script. You could choose the targets for the correlation analysis using online tools suggested by the answer above. There might be good tools which could do all this and much more bioinformatics analysis.
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For studying the role of these receptors in my gene of interest regulation in liver I need to have these cell lines
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Thanks a lot
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We have a nuclear/cytoplasmic fractionation protocol that works well, but the problem is that the isolated nuclei are EXTREMELY sticky and very difficult to work with.
We want to fix these cells, stain for cell-type specific intracellular markers, and FACS sort for RNA-seq. We can do this routinely with whole cells, but isolated nuclei are totally unmanageable.
All buffers are made with Ca/Mg-free PBS, and supplementation of 5mM EDTA does not help. I have also tried treatment with 50U/ml DNase + 5mM MgCl2 to no avail.
Straining cells through a 70um nylon mesh is off the cards, as the nuclei gloops get stuck on the mesh.
Does anyone have ideas/tips and tricks to deal with this problem?
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Hi there. I am working on unfixed nuclei separation from tissue for chromatin studies. What I found was that sucrose in the buffer is essential for the integarity of nuclei, for it helps to maintain the osmatic pressure. 5%-15% sucrose all helps. Mg++ might be also important for the integarity of nuclei. When I simply use PBS, the nuclei don't look good. The DNA was leaking and thus clump them together.
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Hi there,
It has been a long time that I think about one of the important aspects of miRNA research: how many genes mediate miRNA effects? According to the literature, most if not all of miRNAs exert their effects through modulating tens (or hundreds) of mRNA targets (although in different contexts and cell types). For some miRNAs, a small number of key mRNA targets mediate the effects elicited by the miRNA, but for others, a large(r) set of mRNAs are fine-tuned by the miRNA and it is the collective effects of these minor downregulations which lead to a cellular behavior promoted by the miRNA. However, what I see is that almost all of the journals insist on finding a single target for the miRNA of interest! The situation gets more complicated to me when the miRNA influences several behaviors of a cell at the same time (e.g. survival, differentiation, colony formation, migration), yet the reviewer expects authors to find a 'single' target which probably mediates all these diverse effects. Actually, this rationale does not make sense to me, since I think there should be more than one miRNA targets that are mediating the miRNA effects in different cellular contexts.
I would highly appreciate if you comment on my question and let me know what you think in this regard as well as how we should manage a situation where the reviewer requests you to find a single target but you think (or expect) that there should be several miRNA targets, since I think insisting on finding a single target may result in bias (which is not good science).
Best regards,
Sharif
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Hi Sharif
Excellent question and very interesting reflection.
I suffered the same critics from reviewers. Thinking in a very simplistic way, complex eukaryotic organisms are very redundant. So, they have many ways to do the same things. In consequence it should be very difficult to find a "master" miRNA which will regulate a very important gene or pathway. On the other hand, a multiple and complex effect is expected, involving many miRNAs that are working together. Of course that you can find "master" miRNAs in simple organisms, but in humans this is very difficult.
If you want to find interesting miRNAs in a particular process, I would suggest you to use a complex approach, combining information about target recognition and also about pathways. You can distinguish different categories of targeted mRNAs if you pinpoint them into biochemical pathways. More relevant miRNAs will target "receptors" instead of "effectors".
Of course this is not an easy task.. Analysis of many variables is needed. More relevant miRNAs will be the ones that regulate more targets. On the other hand, the most relevant targets will be those regulated with more miRNAs at the same time.
Take a look at this paper where we did this kind of approach.
Best of luck. Waiting for your feedback.
Paco
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Database may or may not contain gene regulation data of other strains.
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Hello Gaurav, DO you know about this 
Hope that will help you. You can use transcription units data. 
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I did RT-PCRs and got several interested genes.  The thing is I want to know the intracelluar pathways that could lead to these genes regulation.
Is someone familiar with this or could someone provide useful tips about that?
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Hi
there are lot of tools, but what you can do is a look on biogps (http://biogps.org/#goto=welcome) , the reactome (http://www.reactome.org) or DAVID (https://david.ncifcrf.gov) to analyze your lists of genes, just to begin. otherwise, my comments match Heena's ones, you should provide more details to get better answers.
fred
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I observed this in one of my microarray experiments in which the first two gene got upregulated and last gene was downregulated. these three genes belonged to the same operon. Kindly suggest
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If you are sure that these genes are in the operon and can confirm these results using qRT-PCR, then the difference can be due transcriptional attenuation, e. g.  premature termination of transcription. Transcriptional termination is one of the mechanisms to regulate gene expression. 
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Hi,
I have 8 different starch samples from stressed wheat (drought and heat). I want to plan an assay for define differences of amounts for amylose and amylopectin.  I have found one assay kit for it but cannot afford the money (kit is for 100 tests and more than 550€ in Turkey). I was looking for some protocols online for wet lab and found 1 about it “iodine complex”. But couldn’t understand the quantification methods. Do you have any suggestions for it?
Thanks,
Deniz.
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The reaction is pretty straight forward. A potassium iodide solution is used as iodine itself is not very soluble and in aqueous solution s the triiodide ion is formed which binds with the spiral structure of the starch molecule and turn to purple-blue color from brown. This blue-black color can easily be measured using a spectrophotometer usually at 600nm. You can easily construct a standard curve using pure starch samples.
As far as a distinction between amylose and amylopectin is concerned, there are some fairly old but tried and tested protocols available that can be used to separate amylose and amylopectin, or if you know the ratio of the two in wheat samples you can get away with measuring just amylose. Also you may need to do a multi-wavelength study to get more accurate results. It can be a bit time consuming but not at all difficult. And yes your concerns about the kits are not unfounded, their prices can be exorbitant but mostly because they are enzyme based.
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We are getting large deletion, although we expecting only small deletion by NHEJ with Cas9 nickase. Between the two sgRNAs is a 22bp gap. The picked & sequenced clones have deletion up to 100bp. Does anyone have an explanation?
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Double nicking in a 22-bp region can generate, in some cases, a "double stranded break" with free DNA-ends like a true (wild type) Cas9-mediated DSB. These ends are targets for exonucleases removing a lot of nucleotides ending up with a 100-bp deletion. 
Getting these free-ended DNA fragments can be generated due to replication or transcription, both of which are in most cases not easily controlled. 
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Dear all,
I want to knock down one protein by 50% in HCC cell lines. I want to know whether it is possible and how to achieve it?
Thanks sincerely for your answer.
Zhou.
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I agree with Joseph Papamatheakis. If you need to maintain this for any length of time, you would have to make a heterozygous null using genome edits tools such as CRISPR/Cas9.
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 Would like to check in vivo if a gene were interested in is indeed flow-regulated. Collaborators will be co-author on the final publication. Your help is highly appreciated
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no,. it is about Tie2
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Hello all,
I am planning to perform a viability drug screen with Selleckchem bioactive compounds library (~2000 drugs). 
My goal is to find drugs that differentially kill cells with  wt or knockout of my gene of interest. Since the potency of drugs varies widely (nM to >50 uM range of IC50) I wonder what is the best design strategy. I saw that people just use 1 uM and/or 10 uM in primary screens but this would miss the relevant range of many drugs, where I have a chance to see the effect of my gene.
Obviously, doing the screen with more concentrations will decrease the replicates for each (I am thinking to use duplicates since CellTiter-GLo gives very tight replicates).
I would appreciate any input regarding the screen design.
Thanks,
Igor
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We do automated high throughput screening in our facility for Chemical Genomics.  For an initial screen, all compounds are used at 10 uM in DMSO.  If you identify a hit, we then do a dose response curve over a broader range from 1 nM to 100 uM. 
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I'm looking for mRNA markers for general IFN response. Also, can the type I and II interferon responses be identified using mRNA expression of defined marker gene sets by qPCR?
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Dear Kristiina,
mRNA markers for  IFN responses can be very cell/tissue specific.
But you can consider the following "general" interferons:
Interferon-α&β Receptor Ligands: IFNA1, IFNA4, IFNB1.
Cytokine Receptor Ligands: IFNA14, IFNA16, IFNA2, IFNA21, IFNA5, IFNA6, IFNA7, IFNA8, IFNE, IL15.
Interferon Related Genes: IFRD1, IFRD2, IFNL2, IFNL1, IL6.
You can also monitor the general Interferon Receptors:
Interferon-α&β Receptors: IFNAR1, IFNAR2.
Hematopoietin & Interferon-Class Receptors: IL10RB, IL11RA, IL12B, IL13RA1, IL20RA, IL21R, IL22RA2, IFNLR1, IL2RB...(there are few more)
Monitoring the "common" Interferon Regulatory Factors may also be a good idea:
IRF1, IRF2, IRF3, IRF4, IRF5, IRF6...
Usually we  initially test a broad range of mRNA markers to ID those best expressed in the specific cell line/tissue.
Good luck!
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Hi,
I'm purifying a recombinant protein. It's secreted protein. After chromatography procedure, I have some samples of protein:
- Fermentation sample (applied sample): the supernatant from BSM medium (pH 7.1 - 7.3, conductivity: 35 mS/cm, approximately)
- Column flow sample: pH 4.0
- Eluted sample: pH 7.0, NaCl 0.9 M, Tris-HCl 20mM,
I see these three protein samples have three different buffer. I want to measure the amount of protein in these samples by Bradford assay method, but I don't know which buffer should I use to balance. I'm using mQ for this step.
Please give me advice. 
Thanks.
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Hi, in the Bradford assay you have to prepare a standard curve, in particular you have a linear range of the assay for your standard protein, for example BSA, between 1 to 20ug or 20-140 ug. In the standard curve you have to add the ul of lysis buffer in which you resuspended your protein of interest. The same ul of buffer the you add to your blank sample. In your situation, if I understand correctly, the buffers are different (prepared with completely different reagents), so you have to prepare a blank and curve samples for each buffers, in this case 3 curves and 3 blanks (all in duplicates at least). Another way, not properly correct, it would be to prepare only a standard curve, without adding any buffers, only water, and prepare at least 3 different blanks.
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I have mouse tissue expression genes, but I  did not found any database or r package for this purpose ?all for human
kindly answer
second I also have lncrna data what kind of ontology or other bioinformatics analysis I can do (mouse data)
?
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For mouse gene ontology analysis, DAVID tool can be used.
Check this review for bioinformatics tools for lncRNA research
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I used genomatyx to analyze transcription factors in promoters sequences, but now I have many problems to login, so does anyone knows another facility to do this?
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Use JASPAR
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It is known that around 1000 TFs are discovered in human cells (bionumbers website). But the statistics about TF-gene interactions are not clarified enough. The answer to this question is crucial in my simulation project. Anybody who could reply to my question based on scientific references would be appreciated as co-author in the final reports. 
Best Wishes,
Mohieddin Jafari
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I read somwhere (I have to find this reference) that a mammalian cell has 5000-6000 expressed genes.
If the human genome has let's say 30000 genes, then around 1/5th of the genes are active in each cell type. And  around 4/5th of the genes then are repressed. Maybe this gives a starting point for some guesstimation work?
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I am trying to knockdown basal level expression of my target microRNA by transfected Anti-Mir,miRNA Inhibitor, but I didn’t get significant  level of knockdown  result by real time PCR.
Have any one any idea please help me?
Conditions.
·         Cell line-MCF12A (The MCF-12A cell line is a non-tumorigenic epithelial cell line). For cell culture I am using  MEGM, Kit Catalog No. CC-3150 by  Lonza/Clonetics with 100 ng/ml cholera toxin.
·         Name of the transfection reagent- lifofectamin 2000(forward transfection),  RNAiMAX(reverse transfection). Transfection down by according to the thermos fisher scientific. I did also forward and reverse but results is same after 24h and also 48h of incubation.
·         For the RNA isolation, used miRCURY RNA isolation kit(EXICON). For cDNA making, used miRCURY LNA universal RT microRNA PCR/Universal cDNA Synthesis kit(exiqon), for real Time PCR, used miRCURY LNA universal RT microRNA PCR/ExiLENT SYBER Green(exiqon). For endogenous control I used U6. Everything I did according to company protocol.
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Locus specific hydroxymethylation quantification using NEB EpiMark Analysis Kit. Does anyone has a template for data analysis using this kit? I want to use raw ct values for my hydroxymethylation analysis and tried to do qpcr but for some samples I don't see any ct values? I am not sure if my conversion protocol failed or my qPCR is not working well. Any suggestions?
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5hmC levels could be very low and not even detectable with qPCR. Did you use the control DNA (5mC, 5hmC and unmodified)? If those gave the expected results, then did you run a qPCR of your fragment of interest without any restriction enzyme? Was the result positive (do you have enough DNA to start with)? NEB Epimark is based on the same technology / concept (beta-glycosylaytion of 5hmC) than Active Motif Specific Chemical Labelling (SCL) precipitation of 5hmC that can also be used for detection at a single locus, except that NEB doesn't use precipitation but 5hmC sensitive restriction enzymes. As a SCL user, I have also been confronted to very high Ct values (> 38) at some loci which are very poorly enriched in 5hmC. How many cycles of qPCR are you doing? I usually run at least 45 cycles. Good luck !
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Dear all
I am going to produce zebrafish knock-in by CRISPR/Cas method. So I want to know proper concentration of CRISPR/Cas components for knock-in (sgRNA, Donor plasmid, Cas9 mRNA). Does anyone have experience with this?
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I can recommend the CRISPR/Cas google group, things like this are discussed there in detail: https://groups.google.com/forum/#!forum/crispr
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We have used 16 S rRNA seq to look at differences in gut microbial composition between patients and controls. Now we want to use qPCR to verify the findings, however, I have only used qPCR before for gene expression, where you use a reference gene to normalise to in order to do relative quant. What do you use when you want to quantify microbial levels?
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Stefanie,
Presumably, you have 16S  primers "specific" for different groups like Bacteroidetes, Firmicutes, Actinobacteria etc. and you are interested in verifying differences in their levels between different samples.  One approach is to use a "universal" 16S primer pair to generate a reference.  This should give you a measure of the "total" 16S DNA in each sample (which may or may  not be closely correlated with the weight of the original stool sample--you could look at that).  Then you are essentially comparing the proportion of each specific group within the total of all 16S sequences in that sample.  This approach is similar to the sequencing approach, which also measures the proportion of each group in the total sample without giving any information on the absolute number of each type.  A general problem with this approach is the specificity of the primers. Ideally, you would include controls for every type of bacteria that you are measuring and assess the degree to which your primers are specific for that type.  This may be a particular concern if you are trying to measure a type that has a low relative content in the total mix and the primers you are using will also weakly amplify a type of bacteria that is common in the total mix. You will not be able to detect a specific signal.
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I want to compare two set of data containing 8 observations and even though they follow a normal distribution, I am not sure it's correct to perform a student-t test on it because the set of data is very small. Or is it better to use a non parametric test?
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The question is: do you expect your data to follow a normal distribution? Do you know from earlier studies or logical reasoning that this kind of data is usually normally distributed?
Normality is an assumption for a t-test, which is no trivial thing. You explicitly "tell" your test that for each group, the further you move away from the mean in either direction, the less likely the observation. If you have good reason to assume that your data is indeed normal, and according to whichever test for normality (they all have their issues, especially with small sample size), your data indeed seems to be normal (or at least kind of symmetrically distributed around the mean), then the t-test is absolutely the way forward. In this way, you will have a lot more power to draw conclusions. 
I argue that for simple questions (I'm not talking about super high dimensional data, or machine learning), parametric testing is to be preferred if you have somewhat of an idea about where your data came from and what kind of distributions you expect.
Many people apply some kind of ad hoc method, where each set of observations is first tested for normality and depending on the outcome, a parametric or non-parametric test is chosen. There are several issues with this method. First, it leads to intellectual laziness by taking away the need for a scientist to wonder what kind of process generated his/her data. Next, it leads to a situation where outliers or deviations from expected distributions are overlooked ("hidden" behind a non-parametric test) and finally, just by the definition of many of those normality-tests, it will lead to the wrong choice of a test in about 5% of cases :)
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In search of articles, I found that neutrophil migration could be blocked by several chemicals. However, the specificity and time and space control is a big issue. Is there any way to specifically block the neutrophil migration?
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Dear Lucia,
The following publications demonstrate specific blocking of the neutrophil migration:
Blood. 2012 Aug 16; 120(7): 1489–1498.
Prepublished online 2012 Jun 1. doi:  10.1182/blood-2012-01-404046
PMCID: PMC3423786
Ly6G ligation blocks recruitment of neutrophils via a β2-integrin–dependent mechanism
Jun-Xia Wang,1 Angela M. Bair,2 Sandra L. King,3 Ruslan Shnayder,1 Ya-Fang Huang,4 Chi-Chang Shieh,4 Roy J. Soberman,2 Robert C. Fuhlbrigge,3,5 and Peter A. Nigrovic 1,5
Author information ► Article notes ► Copyright and License information ►
This article has been cited by other articles in PMC.
 Abstract
Ly6G is a glycosylphosphatidylinositol (GPI)–anchored protein of unknown function that is commonly targeted to induce experimental neutrophil depletion in mice. In the present study, we found that doses of anti-Ly6G Abs too low to produce sustained neutropenia remained capable of inhibiting experimental arthritis, leaving joint tissues free of infiltrating neutrophils. Thioglycollate-stimulated peritonitis was also attenuated. No alteration in neutrophil apoptosis was observed, implicating impaired recruitment. Indeed, Ly6G ligation abrogated neutrophil migration toward LTB4 and other chemoattractants in a transwell system. Exploring the basis for this blockade, we identified colocalization of Ly6G and β2-integrins by confocal microscopy and confirmed close association by both coimmunoprecipitation and fluorescence lifetime imaging microscopy. Anti-Ly6G Ab impaired surface expression of β2-integrins in LTB4-stimulated neutrophils and mimicked CD11a blockade in inhibiting both ICAM-1 binding and firm adhesion to activated endothelium under flow conditions. Correspondingly, migration of β2-integrin–deficient neutrophils was no longer inhibited by anti-Ly6G. These results demonstrate that experimental targeting of Ly6G has functional effects on the neutrophil population and identify a previously unappreciated role for Ly6G as a modulator of neutrophil migration to sites of inflammation via a β2-integrin–dependent mechanism.
In vitro, FPR1-specific antibodies block neutrophil migration
NATURE REVIEWS IMMUNOLOGY | REVIEW
Neutrophil migration in infection and wound repair: going forward in reverse
Sofia de Oliveira,
Emily E. Rosowski & Anna Huttenlocher
Nature Reviews Immunology 16, 378–391 (2016) doi:10.1038/nri.2016.49
Peptide-Mediated Inhibition of Neutrophil Transmigration by
Blocking CD47 Interactions with Signal Regulatory Protein
Yuan Liu,2 * Miriam B. O’Connor,2 * Kenneth J. Mandell,* Ke Zen,* Axel Ullrich,‡
Hans-Jo¨rg Bu¨hring,† and Charles A. Parkos3
CD47, a cell surface transmembrane Ig superfamily member, is an extracellular ligand for signal regulatory protein (SIRP). Interactions between CD47 and SIRP regulate many important immune cell functions including neutrophil (PMN) transmigration. Here we report identification of a novel function-blocking peptide, CERVIGTGWVRC, that structurally mimics an epitope on CD47 and binds to SIRP. The CERVIGTGWVRC sequence was identified by panning phage display libraries on the inhibitory CD47 mAb, C5D5. In vitro PMN migration assays demonstrated that peptide CERVIGTGWVRC specifically inhibited PMN migration across intestinal epithelial monolayers and matrix in a dose-dependent fashion. Further studies using recombinant proteins indicated that the peptide specifically blocks CD47 and SIRP binding in a dose-dependent fashion. Protein binding assays using SIRP domain-specific recombinant proteins demonstrated that this peptide directly bound to the distal-most Ig loop of SIRP, the same loop where CD47 binds. In summary, these findings support the relevance of CD47-SIRP interactions in
regulation of PMN transmigration and provide structural data predicting the key residues involved on the surface of CD47. Such peptide reagents may be useful for studies on experimental models of inflammation and provide a template for the design of anti-inflammatory agents. The Journal of Immunology, 2004, 172: 2578–2585.
The Endogenous Opioid Spinorphin Blocks fMet-Leu-Phe-Induced Neutrophil Chemotaxis by Acting as a Specific Antagonist at the N-Formylpeptide Receptor Subtype FPR
Thomas S. Liang, Ji-Liang Gao, Omid Fatemi, Mark Lavigne, Thomas L. Leto and
Philip M. Murphy1
Laboratory of Host Defenses, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892
Abstract
Spinorphin is an endogenous heptapeptide (leucylvalylvalyltyrosylprolyltryptophylthreonine), first isolated from bovine spinal cord, whose sequence matches a conserved region of β-hemoglobin. Also referred to as LVV-hemorphin-4 and a member of the nonclassical opioid hemorphin family, spinorphin inhibits enkephalin-degrading enzymes and is analgesic. Recently, spinorphin was reported to block neutrophil activation induced by the chemotacticN-formylpeptide N-formylmethionylleucylphenylalanine (fMLF), suggesting a potential role as an endogenous negative regulator of inflammation. Here we use both gain- and loss-of-function genetic tests to identify the specific mechanism of spinorphin action on neutrophils. Spinorphin induced calcium flux in normal mouse neutrophils, but was inactive in neutrophils from mice genetically deficient in the fMLF receptor subtype FPR (N-formylpeptide receptor). Consistent with this, spinorphin induced calcium flux in human embryonic kidney 293 cells transfected with mouse FPR, but had no effect on cells expressing the closely related fMLF receptor subtype FPR2. Despite acting as a calcium-mobilizing agonist at FPR, spinorphin was a weak chemotactic agonist and effectively blocked neutrophil chemotaxis induced by fMLF at concentrations selective for FPR. Spinorphin did not affect mouse neutrophil chemotaxis induced by concentrations of fMLF that selectively activate FPR2. Thus, spinorphin blocks fMLF-induced neutrophil chemotaxis by acting as a specific antagonist at the fMLF receptor subtype FPR.
Therapeutic Effect of Blocking CXCR2 on Neutrophil Recruitment and Dextran Sodium Sulfate-Induced Colitis
Shukkur Muhammed Farooq, RoseMarie Stillie, Majlis Svensson, Catharina Svanborg1, Robert M. Strieter and Andrew W. Stadnyk
Structural Insights into Neutrophilic Migration Revealed by the Crystal Structure of the Chemokine Receptor CXCR2 in Complex with the First PDZ Domain of NHERF
Guorong Lu , Yanning Wu , Yuanyuan Jiang , Shuo Wang, Yuning Hou, Xiaoqing Guan, Joseph Brunzelle, Nualpun Sirinupong, Shijie Sheng, Chunying Li , Zhe Yang
Published: October 2, 2013http://dx.doi.org/10.1371/journal.pone.0076219
Abstract
Neutrophil plays an essential role in host defense against infection, but uncontrolled neutrophilic infiltration can cause inflammation and severe epithelial damage. We recently showed that CXCR2 formed a signaling complex with NHERF1 and PLC-2, and that the formation of this complex was required for intracellular calcium mobilization and neutrophilic transepithelial migration. To uncover the structural basis of the complex formation, we report here the crystal structure of the NHERF1 PDZ1 domain in complex with the C-terminal sequence of CXCR2 at 1.16 Å resolution. The structure reveals that the CXCR2 peptide binds to PDZ1 in an extended conformation with the last four residues making specific side chain interactions. Remarkably, comparison of the structure to previously studied PDZ1 domains has allowed the identification of PDZ1 ligand-specific interactions and the mechanisms that govern PDZ1 target selection diversities. In addition, we show that CXCR2 can bind both NHERF1 PDZ1 and PDZ2 in pulldown experiments, consistent with the observation that the peptide binding pockets of these two PDZ domains are highly structurally conserved. The results of this study therefore provide structural basis for the CXCR2-mediated neutrophilic migration and could have important clinical applications in the prevention and treatment of numerous neutrophil-dependent inflammatory disorders.
Hoping this will be helpful,
Rafik
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So far we tried liposome transfection kit with very low efficiency of success
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Dear Daniele,
I can recommend a transfection reagent called Lullaby Stem for your application
You can find more information here:
If you need a sample, just let me know at tech@ozbiosciences.com
Good Luck
Olivier
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Hello everyone,
I have a colleague that is running a gel electrophoresis and immunoblotting phospholamban, p-phospholamban-Thr17 and p-phospholamban-Ser16 in rat cardiac muscle. She is loading 5 and 10 micrograms of total protein, using 0.18M DTT (fresh), 1xLDS and heating her samples for 30min at 95C.
She aims to dissociate the pentamer into monomer and so, quantify relative amounts of PLB and p-PLBs.
However she can still detect the pentamer with her Ser16 antibody, but not with PLB or Thr 17.
Does anyone have experience with this technique or would like to share your thoughts? That would be very appreciated.
Many thanks.
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Hello Bernard. I do appreciate your attention. 
Thanks for your suggestion, I will discuss this technique with my colleague. I also told her that she can check  the antibody features with the technical support of the company she is buying it from. I don't believe she tried the protocol you have suggested here. Again, many thanks for your help! 
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I am testing zebrafish and Xenopus laevis for reduced hormone levels. It is the same hormone in both species. My method of choice is ELISA. However, when I researched for the available kits, they all state specific reactivity, with only a few  being pan-specific. Shouldn't all kits work similarly at the hormone level, regardless of their species specificity? Any advice would be great. Thank you.
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That means that the hormone is exactly the same, but the interferences in different species are different, so the kit is not useful for all of them. Is that right? Or what are they talking about? It is not clear for me.
But if the kit was already tested for different species, this is the Information you need to know. If the kit has not been tested and everything relies on theoretical predictions, the situation is more complicated, and you could try to see what happens.
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I am working on microglial cells (macrophages from the Central Nervous System). It's really difficult to do transfection (transient, siRN