Investigating living systems at the protein level is continuing to provide important insights into many biological processes across all kingdoms of life. Mass spectrometry based proteomics has fundamentally changed the way in which biological systems are interrogated because of its ability to measure thousands of proteins and post-translational modifications in parallel. This enables investigations at all levels of biological complexity ranging from protein complexes to human patient populations. While five years ago, the majority of proteomic experiments mostly enumerated the protein constituents of a biological system, quantitative measurements are at the heart of practically every proteomic study today. This shift was once more significantly driven by developments in mass spectrometry which is now the de-facto standard for quantitative measurements in proteomics. Alongside, the miniaturization of associated sample preparation and separation techniques as well as the adoption and further development of data analysis strategies from other –omics research have helped transform proteomics from a qualitative to a quantitative science.

At the same time, the areas of life science research to which proteomic methods are being applied are expanding rapidly. While a few years ago, most of the successful proteomic work was performed in rather simple models such as unicellular organisms or cell lines derived of animal and plant origin, it is becoming increasingly possible to work with primary samples including that of human patients. However, scientists engaged in such studies had to realize that the enormous molecular complexity and the dynamic nature of proteomes posed much larger challenges than those encountered for either genome or transcriptome studies. In particular, issues related to splice variants, post-translational modifications, dynamic range of protein expression spanning 10 orders of magnitude, protein stability, transient protein associations, and dependence on cell type or physiological state etc. are still limiting our technical ability to characterize proteomes comprehensively and reproducibly in a reasonable time. Unsurprisingly, numerous experimental strategies and schemes have been devised to address the many challenges and, as in any developing field, some have come and gone, while others have been adopted more broadly. It is probably safe to assume that we have not yet seen the end of the technical developments which, in turn, will allow more and more difficult biological systems to be approached by proteomics.

Despite all the hurdles, mass spectrometry based quantitative proteomics increasingly impacts life science research in many areas including protein expression profiling, the analysis of signaling pathways or the development of protein biomarker assay systems to name a few. It is important to note that in each area, distinct scientific questions are being asked and, therefore, distinct proteomic approaches will have to be applied, many of which vary widely in their versatility, technical maturity, difficulty, and expense. Consequently, we must recognize that some scientific questions are, and will remain, much harder to answer by proteomics than others. Still, the strong trend towards the alternative scientific paradigm of system-level interrogation of biological phenomena is unstoppable and will without doubt continue to provide important complementary views to traditional and still highly successful hypothesis-driven research.

In this special issue on quantitative mass spectrometry in proteomics, we have assembled a group of reputed scientists who all have significant statements to make regarding the topic of this issue. There are eight reviews that provide an in-depth appreciation of a state-of-the-art technology alongside six original research articles highlighting some of the current trends. We can of course not claim to cover the field comprehensively, but do believe that the content of this special issue has a lot to offer, both for newcomers as well as experts in the field of mass spectrometry based proteomics.