slide assay with vista green. It's possible?

GysdeJongh jongh711 at planet.nl
Mon Apr 17 09:15:21 EST 2006


"Peter Ellis" <pjie2 at cam.ac.uk> wrote in message 
news:4a8edjFrol2uU1 at individual.net...
> GysdeJongh wrote:
>> "Peter Ellis" <pjie2 at cam.ac.uk> wrote in message
>> news:4a7l4sFrg5n8U1 at individual.net...
>>> GysdeJongh wrote:
>>>>
>>>> Or you could buy Affi- or ABI chips . Faster .
>>>> They have another advantage : they are the only one accepted for
>>>> publication ! You will not get a publication with home brew chips in
>>>> any serious journal.
>>>
>>> Rubbish
>>
>> This search string :    Ellis P[author] AND (microarray OR Array OR
>> "DNA Array")     in Pubmed finds 3
>> Two different Peters , 1 does not use array's
>> Maybe I am missing something
>
> I'm the one that does use microarrays.
>
> Leaving aside the papers of mine that don't directly hinge on array data, 
> there are four papers I've authored or co-authored since 2004 that fit the 
> bill (publication of array data from home-brew chips).  Your string finds 
> two of them.  One is new enough not to be indexed in PubMed yet, the 
> fourth simply didn't have "microarray" as a keyword.  Amazingly enough, 
> I'm more likely to put things like "spermatogenesis" or "testis" as 
> keywords, since the novel scientific content of a paper is by and large 
> the important bit - perhaps this is why you think there are no microarray 
> papers out there.
>
> These four papers are in Molecular Human Reproduction, Human Molecular 
> Genetics, Genome Biology and Mol. Cell. Biol.  OK, none of them are Nature 
> (and I certainly don't want to sound like I'm boasting) - but I think that 
> all four could be considered serious journals.
>
> I'm not *remotely* interested in getting into a dick size war about the 
> length of respective publication records: I'm just making the point that 
> home-brew array work *does* get published in good journals.  That is, if 
> it's good work, supported by other evidence, that tells us something 
> interesting about the world - same as any other array work on any other 
> array platform.
>
> I note in passing that trying this search string:
> "cdna microarray" NOT affymetrix NOT ABI
> in PubMed finds 2253 papers.  Why not try reading some?  You might be 
> pleasantly surprised.

Hi Peter ,
thanks for your kind reply.
For me this is an important issue.
Sorry if this post is a bit long.

I know a Peter Ellis from his numerous good posts in the Yahoo microarray 
group . I like to read his very factual posts. Sorry if I mix things up 
:(  I am here : http://www.skin-lab-nijmegen.nl/  We are a small group . Me 
, a colleague , most of the time one postdoc and one or two students . I 
begin my day by starting SAS , my colleague by staring at the NCBI website , 
then we meet at the coffee machine to discuss how we can survive today . 
Which always means budget , which always means publications .

We are interested in skin deseases . We were looking into the genes that 
might cause Psoriasis from the beginning . We constructed two SAGE libraries 
one is here : PMID: 15502200 and here PMID: 11991716 .

We were in the microarrays from the beginning . We bought a simple printer , 
a scanner , 1000 clones from the RZPD and constructed a "Skinchip". This was 
not a trival task . 30 % of the RZPD clones gave no product , more than 1 
product or were retracted . In the end the "Skinchip" had about 750 genes . 
On most of the chips we saw 1 spot instead of 750 also known as background. 
Or no signal in the Cy5 channel also known as Cy5 degradation by ozone. The 
Skinchip produced zero articles.

The guy that did a promotion in our lab moved to the Microarray Facility. 
The Microarray Facility had just been funded by our university. Lots of 
venture capital . The idea was , ofcourse , that this technique was so 
sofisticated that a specialists group was necessary for advice and the 
printed and UV-cross linked chips . They had a good statistician , a 
bioinformatician and a number of technicians that mastered the microarray 
technique. Even they had not enough money to buy a good oligo library. They 
bought the 20,000 gene library from Compugen  with three other 
universities.The library was good , little confusion about the gene 
annotation .We got the chips from them , did the hybridisations and 
statistics ourselves. After about a year we could produce hybs with little 
background and reasonable signal. Then we suddenly got chips with 
"fragmented spots" . The DNA fall off . This was due to conditions during 
printing. The microarray facility now bought his fourth generation printer 
and placed it in a special clean room with defined temperature , humidity 
and monitored ozone level . It began to look like a real chip facility . By 
that time we got ineresting results ; a list of 180 regulated genes . Some 
checked with QPCR , some checked on protein level . We could not get a 
publication accepted , they keep nagging.

Our microarray facility also changed a lot.My friend now runs the place. He 
is a good biologist but also a good manager . He cleared out the whole lab 
in just one day. Now there are labels "Affymetrix" everywhere . There are 
now 2 statistitians and 3 bioinformaticians. There is no printer. No body 
except  the very skilled technitians enters the lab ; you may handover yout 
RNA at the door . Compugen is doing something else , they nolonger sell the 
ologo library.

By that time I wandered are we clumsy ? Can other people do this ? So I have 
done this already :

> I note in passing that trying this search string:
> "cdna microarray" NOT affymetrix NOT ABI
> in PubMed finds 2253 papers.  Why not try reading some?  You might be 
> pleasantly surprised.

The surprise was indeed pleasant : we were not alone. We both know that the 
word "Affymetrix" could still be only in the methods section where this 
search does not look. I  _did_  look at all the papers I could find by the 
search above and other variations. I found two types : 1) home brew chips by 
a large microarray facility adressing a technical issue , 2) home brew chips 
by a large microarray facility working very closely together with a large 
biomedical group adressing an interesting biomedical issue. I found zero 
articles by a small group as ours hybridizing chips made by themselves or 
even utilizing chips spotted for them by a large microarray facility.

In the mean time these were key publications for us : PMID: 14657882 , 
PMID: 12960356 , PMID: 12644634 , all Affymetrix . Now have a close look at 
the last : this is a very large biomedical group close to the inventors : 
Department of Biostatistics, Harvard University, Boston  . They also still 
use Affy chips .

I discovered these things :
1) The beginnig of the microarray experiment is high throughput . But the 
textminig like Onto express is still low throughput. There is no artificial 
intelligent software that extracts the cause of a desease from Pubmed with a 
list of regulated genes as input. The reason is , ofcourse , that the 
information is not yet there.

2)This departement does skin research for the last 30 years but we never 
heard of the highest regulated genes we found , not much was known about 
them in Pubmed.

Conclusion : there is a niche for small groups like us : avoid the 
microarray experiments concentrate on the molecular biology of one or two of 
the vast number of regulated genes found by the large microarray facilities 
. We left the microarray business.We did not try to publish the results 
directly. We might submit them to a public data bank . We use the list of 
regulated genes ourselves .We now concentrate on the biology of one or two 
genes. This can be published : PMID: 16565075 , PMID: 16354186

We greatly underestimated the technical difficulties , the time and money 
needed for a microarray experiment . If I had to do this again I would give 
my purified RNA to a microarray facility that uses Affy chips and waited for 
the annotated list of regulated genes.Then I would start with that list . 
This would save me 80 % of the time and the cost of the project .

I realize that everybody has to decide for himself.
I realize that this is just a movie I project to the inside of my skull.
I realize that I might be wrong.

But...
Please have a look at one of the many investigations that address the 
reproducibility of microarrays.Please note that this was conducted by a 
large group of specialists : microarray facilities.

Nat Methods. 2005 May;2(5):351-6. Epub 2005 Apr 21.

Standardizing global gene expression analysis between laboratories and 
across platforms.

To facilitate collaborative research efforts between multi-investigator 
teams using DNA microarrays, we identified sources of error and data 
variability between laboratories and across microarray platforms, and 
methods to accommodate this variability. RNA expression data were generated 
in seven laboratories, which compared two standard RNA samples using 12 
microarray platforms. At least two standard microarray types (one spotted, 
one commercial) were used by all laboratories. Reproducibility for most 
platforms within any laboratory was typically good, but reproducibility 
between platforms and across laboratories was generally poor. 
Reproducibility between laboratories increased markedly when standardized 
protocols were implemented for RNA labeling, hybridization, microarray 
processing, data acquisition and data normalization. Reproducibility was 
highest when analysis was based on biological themes defined by enriched 
Gene Ontology (GO) categories. These findings indicate that microarray 
results can be comparable across multiple laboratories, especially when a 
common platform and set of procedures are used.

PMID: 15846362

Quote from this article :
The results demonstrate that the highes level of reproducibility between 
laboratories was observed when a commercial microarray was used.

The results indicate that more than half of the variability in these data is 
attributed to the microarray

Have a look at page 3
The plots of the commercial array's are lines , the plots of the spotted 
arrays are blobs. The Correlations of the commercial arrays are nice , red , 
significant . The correlations of the spotted arrays are , depressive , 
black , non-significant.

Your peers reviewing your paper for publication are also reading Nature....
As said it's my movie....
I might be wrong....

When I saw the question of the OP I thought : he/she is underestimating 
something

My sincere advice :
If you are a small group of biologists and you want do to microarrays then 
look for a microarray facility at your university . Start talking to the 
bioinformatics and statistics guys even before you fill the first eppendorf 
. Work as closely together as you can .If they offer the service than give 
them your purified RNA and just wait for the annotated list of regulated 
genes. Than start from there. If your university does not have a large 
microarray facility look for a commercial solution.

hth
Gys




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