MultiOmics might be my favorite word right now. I'm not the only one who is digging it. Lots of papers seem to have this new word in the title right now. And with good reason! We've got so many ways of globally profiling what is in the cell that the next trick is going to be integrating all of them!
For an oddly satisfying review of the topic, you should check out this open access study in Nature Communications. In the blog title, I'm going to leave the term "oddly satisfying." I'm not sure what it is -- is it the way this article rapidly tears through all sorts of -omics things? Is it the nice bold lines used for the illustrations that remind me of an Archer cartoon? Is it the cold medicine that has been slowing my brain down? I'm not entirely sure. What am I writing?
What I do know for certain is that, while this is an original study on the multiomics of E. coli it reads a whole lot like a review, cause it knows it has to introduce the reader to at least one -- if not many, of the things they're looking at. It also reads that way because this is almost entirely a meta-analysis of data from repositories. They do appear to do some of their own transcriptomics. Cause, you know, nobody's ever done RNASeq on E. coli before (though, more likely because it was easier to run their own samples than to download someone else's 2TB or RAW data).
In the end, though, the best part is that it shows how all these technologies are complementary. They can detect problems in their bacterial test system from data at the protein and protein structural level as well as in the fluxomics and at some of the transcriptional stuff. Key points here -- sure you get extra info from all these other techniques -- but it doesn't mean you have to do them to get to your answer! There are many ways to get to the same answers!