I am planning some experiments to investigate how mono cultures of microbes respond to different nutrient concentrations. I want to use an -omics based approach to understand how, on a molecular level, the microbes utilise these nutrients by looking for up regulation of associated genes. With the idea looking out for upregulation in mind, I was going to go for transcriptomics. But now I am beginning to realise that regulatory changes in genes does not necessarily translate to the molecular utilisation of a nutrient by a cell. To that end, perhaps I would be better using quantitative proteomics to capture changes in the concentration of functional proteins which are actually interacting with the nutrients. However, I worry that by relying on proteomics I might miss important regulatory changes for microbe species where the proteome is less well defined.

I should say that it's an either/or situation, there is only budget for one. I'd appreciate any thoughts on the best approach. Thanks.

  • $\begingroup$ You might reach a greater audience at biostars.org. Do you have access or a potential collaboration with a group that can run the high-throughput proteomics? RNA-seq is simple, one might even say trivial these days, both if you do the libraries yourself or just send the RNA to a facility while proteomics is a bit less standard I think, at least we had get in contact with a collaborator to get some proteome-wide experiments going, both because we lack experience and most importantly the machinery (HPLC, MS and everything around it). $\endgroup$
    – ATpoint
    Aug 17 at 9:24
  • $\begingroup$ My gut feeling is that you will be figuring out a lot more causality using the transcriptomic approach, but that might be just because I am a lot more familiar with that type of data. This is a really open-ended question I think, a lot more suited to discussion forums than Q&A sites. $\endgroup$
    – Kamil S Jaron
    Aug 17 at 15:18
  • $\begingroup$ I agree that this is a discussion question. Proteomics is less available but also less sensitive, albeit requiring less corrections analysis-wise. For transcription factors and other low copy number protein transcriptomics is the best option. Bacteria do not go around sequestering mRNA as much as Eukaryotes, which is nice, but some phyla, produce compounds that make them problematic for RNA work (e.g. the osmolyte in Firmicutes spores (something-picolinate)), so proteomics > transcriptomics for Geobacillus etc. Also... there is metabolomics if enzymes are involved (but way less sensitive). $\endgroup$ Aug 17 at 15:25
  • $\begingroup$ Also, before starting any -omics, check the quality of your reference genome if it is a non-standard species. This sounds unimportant, but if your have an auto-annotated reference genome, you will spend more time fixing it than anything else —e.g. pathway X is missing enzyme Y, but in the operon with WYZ there is a mystery enzyme, which guilty by association would suggest is a candidate, but you have to get more evidence. $\endgroup$ Aug 17 at 15:33
  • $\begingroup$ @MatteoFerla Thanks for this. When you say quality, are you referring to coverage? The species I'm interested in has a reference genome with 39% coverage, is that likely to be sufficient? $\endgroup$
    – phytofan
    Aug 18 at 13:30

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