Traditional means to study proteins - Mass spectrometry

A proteome is the full set of proteins within a given entity such a cell or an entire organism. A cell’s particular proteomic make-up, including individual protein abundances and locations, determines its identity and function at the molecular level. Thus, mapping a cell’s proteome provides mechanistic information on biological activities and makes it possible to hypothesize the mechanisms behind biological activities and disease states in human health. Indeed, knowledge of the proteome may lead to a broad range of discoveries and applications including everything from new therapeutics to new ways to protect plants from drought.

Given the essential importance of the proteome, scientists have been developing ways to study it for many years. In this “Traditional approaches to study proteins” series, we cover the basics of traditional means to study the proteins that make up the proteome. “Omics” scale technologies generally aim to measure all or a large amount of a particular type of biological molecule in a sample. Most of the techniques discussed here are not strictly omics technologies as they do not enable scientists to acquire data on a large portion of the proteome at once. Nonetheless, they form the foundations upon which proteomics technologies have been built. In our “Next generation proteomics technologies” series, we dive into the technical concepts behind emerging omics technologies, which aim to enable scientists to study the full proteome.

In the graphics portraying the technologies in this series, we provide qualitative assessments of proteome coverage and ease-of-use. Technologies with low proteome coverage are generally used for targeted experiments looking at a small number of proteins at once. Medium coverage technologies can look at 100s to 1000s of proteins in a single experiment. Truly comprehensive, high proteome coverage technologies can analyze tens of thousands of proteins at once.

Low ease-of-use technologies generally require complicated, difficult, or customized sample preparation involving a lot of hands-on experimenter time, and their data may be difficult to analyze or require bioinformatics support. High ease-of-use technologies employ simple, standardized sample preparation, include more automation, and provide simple, data-rich outputs including protein abundance. Medium ease-of-use technologies have some mix of these attributes.

In addition to assessing standard metrics like these, we also discuss some of the pros and cons of each technology. Many of the pros and cons discussed below are specific to the capabilities of the technology.

Importantly, the technology assessments here should not be viewed as definitive. Rather, they aim to help you think about how you can best leverage these technologies for your specific experimental goals.

Mass spectrometry

Mass spectrometry (mass spec) has been one of the main tools of proteomics for many years. While there are many versions of mass spec, they generally involve:
 

• The extraction of proteins from a biological sample
• Digestion of proteins into peptides
• Giving the peptides an electric charge
• Passing the charged peptides through a device where they travel at a certain rate based on their mass and charge
• Breaking separated peptides apart into small fragments
• Passing the fragments through a device that separates them according to mass and charge again
• Allowing the separated fragments to hit a detector, generating spectra, which display the number of fragments of different masses/charges that hit the detector
• Computational matching of the generated spectra to known or predicted spectra for specific proteins 

The researcher is provided with a list of proteins in their sample. Researchers can also use mass spectra to measure the relative abundance of the identified proteins.
 

As you might imagine, some proteins can generate very similar spectra and/or may not be separated well because they have similar masses and charges. In addition, signals from high abundance proteins can often drown out signals from low abundance proteins. Thus, even with extensive optimization, mass spectrometry can only measure a fraction of the proteome.
 

Researchers can complement mass spectrometry with a variety of techniques that make the spectra easier to analyze. For instance, prior to entering the mass spectrometer, researchers can pass their proteins or digested proteins (peptides) through separation columns. These columns are tubes containing porous materials that separate proteins or peptides based on properties like size or hydrophobicity. Separations can be accomplished off-line, where a single sample is separated into multiple fractions and each fraction is analyzed separately. Alternatively, in-line separation applies a single sample to the separation column and the proteins or peptides exiting the column can directly enter a mass spectrometer. Protein or peptide analytes are sequentially analyzed by the mass spectrometer based on how they interact with the column. As only a fraction of the proteins or peptides in the sample are exiting the column at any point in time, the mass spectrometer can focus analysis on a smaller number of analytes increasing detection and quantitation resolution.
 

While there are many techniques that can ultimately make the resulting spectra easier to analyze, they introduce biases into the protein detection process. For instance, some proteins may be incompatible with certain columns. Thus, these time-consuming processes may limit the amount of data researchers get from mass spectrometry in one experiment. 

Pros: 

• Omics-scale – While mass spectrometry cannot provide measurements of the full proteome, it can provide data on thousands of proteins at once. This provides more comprehensive information than the other techniques discussed in this series.
   
• It is possible to detect peptide modifications – Although the data analysis can be difficult, mass spectrometry can be used to identify proteins that have been modified through such biological processes as phosphorylation and glycosylation.

Cons:  

• Low dynamic range – Signals from high abundance proteins can drown out those from low abundance proteins making potentially very important proteins difficult to analyze.
   
• Peptide-based inference of protein identity – This technique infers protein identity by compiling the sequences of multiple component peptides. Such inferences can be inaccurate if multiple protein species in a sample are composed of similar peptides.
   

• Cost – Mass spectrometers are very expensive.
   
• Low ease-of-use – Protein preparation for mass spectrometry may need to be highly customized depending upon the sample type and what fraction of the proteome researchers wish to study. Mass spectrometers themselves also have a high learning curve and the spectra they generate must be analyzed by specialized software. 

Despite its limitations, mass spectrometry has been, for many years, the main tool available to researchers wishing to analyze more and more of the proteome. It has been used to make many biological discoveries and develop many therapeutics. It is also continually being improved through instrumentation developments, new, innovative methods, and improved software for data analysis.

To overcome some of the drawbacks of mass spectrometry, many researchers are developing new technologies that will make it easier to comprehensively analyze the proteome. We discuss the concepts behind some of these up-and-coming technologies, including our own platform, in other “Proteomics” posts.