Editing Proteomics (section)

==Methods of studying proteins==
In proteomics, there are multiple methods to study proteins. Generally, proteins may be detected by using either [[Antibody|antibodies]] (immunoassays), electrophoretic separation or [[mass spectrometry]]. If a complex biological sample is analyzed, either a very specific antibody needs to be used in quantitative dot blot analysis (QDB), or biochemical separation then needs to be used before the detection step, as there are too many analytes in the sample to perform accurate detection and quantification.

=== Protein detection with antibodies (immunoassays) ===
[[Antibodies]] to particular proteins, or their modified forms, have been used in [[biochemistry]] and [[cell biology]] studies. These are among the most common tools used by molecular biologists today. There are several specific techniques and protocols that use antibodies for protein detection. The [[enzyme-linked immunosorbent assay]] (ELISA) has been used for decades to detect and quantitatively measure proteins in samples.  The [[western blot]] may be used for detection and quantification of individual proteins, where in an initial step, a complex protein mixture is separated using [[SDS-PAGE]] and then the protein of interest is identified using an antibody.{{citation needed|date=April 2023}}

Modified proteins may be studied by developing an [[antibody]] specific to that modification. For example, some antibodies only recognize certain proteins when they are tyrosine-[[phosphorylated]], they are known as phospho-specific antibodies. Also, there are antibodies specific to other modifications. These may be used to determine the set of proteins that have undergone the modification of interest.{{citation needed|date=April 2023}}

Immunoassays can also be carried out using recombinantly generated immunoglobulin derivatives or synthetically designed protein scaffolds that are selected for high antigen specificity. Such binders include single domain antibody fragments (Nanobodies),<ref>{{cite journal | vauthors = Arbabi Ghahroudi M, Desmyter A, Wyns L, Hamers R, Muyldermans S | title = Selection and identification of single domain antibody fragments from camel heavy-chain antibodies | journal = FEBS Letters | volume = 414 | issue = 3 | pages = 521–526 | date = September 1997 | pmid = 9323027 | doi = 10.1016/S0014-5793(97)01062-4 | s2cid = 5988844 | doi-access = free | bibcode = 1997FEBSL.414..521A }}</ref> designed ankyrin repeat proteins (DARPins)<ref>{{cite journal | vauthors = Stumpp MT, Binz HK, Amstutz P | title = DARPins: a new generation of protein therapeutics | journal = Drug Discovery Today | volume = 13 | issue = 15–16 | pages = 695–701 | date = August 2008 | pmid = 18621567 | doi = 10.1016/j.drudis.2008.04.013 }}</ref> and aptamers.<ref>{{cite journal | vauthors = Jayasena SD | title = Aptamers: an emerging class of molecules that rival antibodies in diagnostics | journal = Clinical Chemistry | volume = 45 | issue = 9 | pages = 1628–1650 | date = September 1999 | pmid = 10471678 | doi = 10.1093/clinchem/45.9.1628 | doi-access = free }}</ref>

Disease detection at the molecular level is driving the emerging revolution of early diagnosis and treatment. A challenge facing the field is that protein biomarkers for early diagnosis may be present in very low abundance. The lower limit of detection with conventional immunoassay technology is the upper femtomolar range (10<sup>−13</sup> M). Digital immunoassay technology has improved detection sensitivity three logs, to the attomolar range (10<sup>−16</sup> M). This capability has the potential to open new advances in diagnostics and therapeutics, but such technologies have been relegated to manual procedures that are not well suited for efficient routine use.<ref>{{cite journal | vauthors = Wilson DH, Rissin DM, Kan CW, Fournier DR, Piech T, Campbell TG, Meyer RE, Fishburn MW, Cabrera C, Patel PP, Frew E, Chen Y, Chang L, Ferrell EP, von Einem V, McGuigan W, Reinhardt M, Sayer H, Vielsack C, Duffy DC | display-authors = 6 | title = The Simoa HD-1 Analyzer: A Novel Fully Automated Digital Immunoassay Analyzer with Single-Molecule Sensitivity and Multiplexing | journal = Journal of Laboratory Automation | volume = 21 | issue = 4 | pages = 533–547 | date = August 2016 | pmid = 26077162 | doi = 10.1177/2211068215589580 | doi-access = free }}</ref>

=== Antibody-free protein detection ===
While protein detection with antibodies is still very common in molecular biology, other methods have been developed as well, that do not rely on an antibody. These methods offer various advantages, for instance they often are able to determine the sequence of a protein or peptide, they may have higher throughput than antibody-based, and they sometimes can identify and quantify proteins for which no antibody exists.

==== Detection methods ====
One of the earliest methods for protein analysis has been [[Edman degradation]] (introduced in 1967) where a single [[peptide]] is subjected to multiple steps of chemical degradation to resolve its sequence. These early methods have mostly been supplanted by technologies that offer higher throughput.{{citation needed|date=April 2023}}

More recently implemented methods use [[mass spectrometry]]-based techniques, a development that was made possible by the discovery of "soft ionization" methods developed in the 1980s, such as [[matrix-assisted laser desorption/ionization|matrix-assisted laser desorption/ionization (MALDI)]] and [[electrospray ionization|electrospray ionization (ESI)]]. These methods gave rise to the [[Top-down proteomics|top-down]] and the [[bottom-up proteomics]] workflows where often additional separation is performed before analysis (see below).

==== Separation methods ====
For the analysis of complex biological samples, a reduction of sample complexity is required. This may be performed off-line by [[SDS-PAGE|one-dimensional]] or [[Two-dimensional gel electrophoresis|two-dimensional]] separation. More recently, on-line methods have been developed where individual peptides (in bottom-up proteomics approaches) are separated using [[reversed-phase chromatography]] and then, directly ionized using [[electrospray ionization|ESI]]; the direct coupling of separation and analysis explains the term "on-line" analysis.

=== Hybrid technologies ===
Several hybrid technologies use antibody-based purification of individual analytes and then perform mass spectrometric analysis for identification and quantification. Examples of these methods are the
[[mass spectrometric immunoassay|MSIA (mass spectrometric immunoassay)]], developed by Randall Nelson in 1995,<ref name="NelsonKrone1995">{{cite journal | vauthors = Nelson RW, Krone JR, Bieber AL, Williams P | title = Mass spectrometric immunoassay | journal = Analytical Chemistry | volume = 67 | issue = 7 | pages = 1153–1158 | date = April 1995 | pmid = 15134097 | doi = 10.1021/ac00103a003 | osti = 1175578 }}</ref> and the SISCAPA (Stable Isotope Standard Capture with Anti-Peptide Antibodies) method, introduced by Leigh Anderson in 2004.<ref>{{cite web |url=https://www.broadinstitute.org/scientific-community/science/platforms/proteomics/siscapa |title= SISCAPA, Stable Isotope Standard Capture with Anti-Peptide Antibodies | date = 2015 | work = Broad Institute of MIT and Harvard |access-date=2015-07-15 |url-status=dead |archive-url=https://web.archive.org/web/20150715102826/https://www.broadinstitute.org/scientific-community/science/platforms/proteomics/siscapa |archive-date=2015-07-15 }}</ref>

===Current research methodologies===
Fluorescence two-dimensional differential gel electrophoresis (2-D DIGE)<ref name=Tonge01/> may be used to quantify variation in the 2-D DIGE process and establish statistically valid thresholds for assigning quantitative changes between samples.<ref name=Tonge01>{{cite journal | vauthors = Tonge R, Shaw J, Middleton B, Rowlinson R, Rayner S, Young J, Pognan F, Hawkins E, Currie I, Davison M | display-authors = 6 | title = Validation and development of fluorescence two-dimensional differential gel electrophoresis proteomics technology | journal = Proteomics | volume = 1 | issue = 3 | pages = 377–396 | date = March 2001 | pmid = 11680884 | doi = 10.1002/1615-9861(200103)1:3<377::AID-PROT377>3.0.CO;2-6 | s2cid = 22432028 }}</ref>

Comparative proteomic analysis may reveal the role of proteins in complex biological systems, including reproduction. For example, treatment with the insecticide triazophos causes an increase in the content of brown planthopper (''Nilaparvata lugens'' (Stål)) male accessory gland proteins (Acps) that may be transferred to females via mating, causing an increase in fecundity (i.e. birth rate) of females.<ref>{{cite journal | vauthors = Wang LP, Shen J, Ge LQ, Wu JC, Yang GQ, Jahn GC |title=Insecticide-induced increase in the protein content of male accessory glands and its effect on the fecundity of females in the brown planthopper, ''Nilaparvata lugens'' Stål (Hemiptera: Delphacidae)  |journal=Crop Protection |volume=29 |issue=11 |pages=1280–5 |date=November 2010 |doi=10.1016/j.cropro.2010.07.009 |bibcode=2010CrPro..29.1280W }}</ref> To identify changes in the types of accessory gland proteins (Acps) and reproductive proteins that mated female planthoppers received from male planthoppers, researchers conducted a comparative proteomic analysis of mated ''N. lugens'' females.<ref name="Ge et al 2011">{{cite journal | vauthors = Ge LQ, Cheng Y, Wu JC, Jahn GC | title = Proteomic analysis of insecticide triazophos-induced mating-responsive proteins of Nilaparvata lugens Stål (Hemiptera: Delphacidae) | journal = Journal of Proteome Research | volume = 10 | issue = 10 | pages = 4597–4612 | date = October 2011 | pmid = 21800909 | doi = 10.1021/pr200414g }}</ref> The results indicated that these proteins participate in the reproductive process of ''N. lugens'' adult females and males.<ref name="Ge et al 2011" />

Proteome analysis of ''Arabidopsis peroxisomes''<ref name=Reumann11/> has been established as the major unbiased approach for identifying new peroxisomal proteins on a large scale.<ref name=Reumann11>{{cite journal | vauthors = Reumann S | title = Toward a definition of the complete proteome of plant peroxisomes: Where experimental proteomics must be complemented by bioinformatics | journal = Proteomics | volume = 11 | issue = 9 | pages = 1764–1779 | date = May 2011 | pmid = 21472859 | doi = 10.1002/pmic.201000681 | s2cid = 20337179 }}</ref>

There are many approaches to characterizing the human proteome, which is estimated to contain between 20,000 and 25,000 non-redundant proteins. The number of unique protein species likely will increase by between 50,000 and 500,000 due to RNA splicing and proteolysis events, and when post-translational modification also are considered, the total number of unique human proteins is estimated to range in the low millions.<ref>{{cite journal | vauthors = Uhlen M, Ponten F | title = Antibody-based proteomics for human tissue profiling | journal = Molecular & Cellular Proteomics | volume = 4 | issue = 4 | pages = 384–393 | date = April 2005 | pmid = 15695805 | doi = 10.1074/mcp.R500009-MCP200 | doi-access = free }}</ref><ref>{{cite journal | vauthors = Jensen ON | title = Modification-specific proteomics: characterization of post-translational modifications by mass spectrometry | journal = Current Opinion in Chemical Biology | volume = 8 | issue = 1 | pages = 33–41 | date = February 2004 | pmid = 15036154 | doi = 10.1016/j.cbpa.2003.12.009 }}</ref>

In addition, the first promising attempts to decipher the proteome of animal tumors have recently been reported.<ref name="Klopfleisch1"/>
This method was used as a functional method in ''[[Macrobrachium rosenbergii]]'' protein profiling.<ref name="Alinejad_2015">{{cite journal | vauthors = Alinejad T, Bin KQ, Vejayan J, Othman RY, Bhassu S | title = Proteomic analysis of differentially expressed protein in hemocytes of wild giant freshwater prawn Macrobrachium rosenbergii infected with infectious hypodermal and hematopoietic necrosis virus (IHHNV) | journal = Meta Gene | volume = 5 | issue = | pages = 55–67 | date = September 2015 | pmid = 26106581 | pmc = 4473098 | doi = 10.1016/j.mgene.2015.05.004 }}</ref>

===High-throughput proteomic technologies===
Proteomics has steadily gained momentum over the past decade with the evolution of several approaches. Few of these are new, and others build on traditional methods. Mass spectrometry-based methods, affinity proteomics, and micro arrays are the most common technologies for large-scale study of proteins.

====Mass spectrometry and protein profiling====
{{main|Mass spectrometry}}
[[File:Thermo - Finnigan LCQ Mass Spectrometer (15797493459).jpg|thumb|LCQ Mass Spectrometer used in mass spectrometry.]]
There are two mass spectrometry-based methods currently used for [[Proteomic profiling|protein profiling]]. The more established and widespread method uses high resolution, two-dimensional electrophoresis to separate proteins from different samples in parallel, followed by selection and staining of differentially expressed proteins to be identified by mass spectrometry. Despite the advances in 2-DE and its maturity, it has its limits as well.
The central concern is the inability to resolve all the proteins within a sample, given their dramatic range in expression level and differing properties. The combination of pore size, and protein charge, size and shape can greatly determine migration rate which leads to other complications.<ref name="Weston & Hood 2004">{{cite journal | vauthors = Weston AD, Hood L | title = Systems biology, proteomics, and the future of health care: toward predictive, preventative, and personalized medicine | journal = Journal of Proteome Research | volume = 3 | issue = 2 | pages = 179–196 | year = 2004 | pmid = 15113093 | doi = 10.1021/pr0499693 | citeseerx = 10.1.1.603.4384 }}</ref>

The second quantitative approach uses stable isotope tags to differentially label proteins from two different complex mixtures.<ref>{{Citation |last1=Rozanova |first1=Svitlana |title=Quantitative Mass Spectrometry-Based Proteomics: An Overview |date=2021 |work=Quantitative Methods in Proteomics |volume=2228 |pages=85–116 |editor-last=Marcus |editor-first=Katrin |place=New York, NY |publisher=Springer US |language=en |doi=10.1007/978-1-0716-1024-4_8 |isbn=978-1-0716-1023-7 |last2=Barkovits |first2=Katalin |last3=Nikolov |first3=Miroslav |last4=Schmidt |first4=Carla |last5=Urlaub |first5=Henning |last6=Marcus |first6=Katrin |series=Methods in Molecular Biology |pmid=33950486 |s2cid=233740602 |editor2-last=Eisenacher |editor2-first=Martin |editor3-last=Sitek |editor3-first=Barbara|doi-access=free }}</ref><ref>{{Citation |last1=Nikolov |first1=Miroslav |title=Quantitative Mass Spectrometry-Based Proteomics: An Overview |date=2012 |url=https://link.springer.com/10.1007/978-1-61779-885-6_7 |work=Quantitative Methods in Proteomics |volume=893 |pages=85–100 |editor-last=Marcus |editor-first=Katrin |access-date=2023-04-14 |place=Totowa, NJ |publisher=Humana Press |language=en |doi=10.1007/978-1-61779-885-6_7 |isbn=978-1-61779-884-9 |last2=Schmidt |first2=Carla |last3=Urlaub |first3=Henning|series=Methods in Molecular Biology |pmid=22665296 |hdl=11858/00-001M-0000-000F-C327-D |s2cid=33009117 |hdl-access=free }}</ref> Here, the proteins within a complex mixture are labeled isotopically first, and then digested to yield labeled peptides. The labeled mixtures are then combined, the peptides separated by multidimensional liquid chromatography and analyzed by tandem mass spectrometry. Isotope coded affinity tag (ICAT) reagents are the widely used isotope tags. In this method, the cysteine residues of proteins get covalently attached to the ICAT reagent, thereby reducing the complexity of the mixtures omitting the non-cysteine residues.

[[Quantitative proteomics]] using stable isotopic tagging is an increasingly useful tool in modern development. Firstly, chemical reactions have been used to introduce tags into specific sites or proteins for the purpose of probing specific protein functionalities. The isolation of phosphorylated peptides has been achieved using isotopic labeling and selective chemistries to capture the fraction of protein among the complex mixture. Secondly, the ICAT technology was used to differentiate between partially purified or purified macromolecular complexes such as large RNA polymerase II pre-initiation complex and the proteins complexed with yeast transcription factor. Thirdly, ICAT labeling was recently combined with chromatin isolation to identify and quantify chromatin-associated proteins. Finally ICAT reagents are useful for [[proteomic profiling]] of cellular organelles and specific cellular fractions.<ref name="Weston & Hood 2004"/>

Another quantitative approach is the accurate mass and time (AMT) tag approach developed by [[Richard D. Smith]] and coworkers at [[Pacific Northwest National Laboratory]]. In this approach, increased throughput and sensitivity is achieved by avoiding the need for tandem mass spectrometry, and making use of precisely determined separation time information and highly accurate mass determinations for peptide and protein identifications.

==== Affinity proteomics ====
Affinity proteomics uses antibodies or other affinity reagents (such as oligonucleotide-based aptamers) as protein-specific detection probes.<ref>{{cite journal | vauthors = Stoevesandt O, Taussig MJ | title = Affinity proteomics: the role of specific binding reagents in human proteome analysis | journal = Expert Review of Proteomics | volume = 9 | issue = 4 | pages = 401–414 | date = August 2012 | pmid = 22967077 | doi = 10.1586/epr.12.34 | s2cid = 19727645 }}</ref> Currently this method can interrogate several thousand proteins, typically from biofluids such as plasma, serum or cerebrospinal fluid (CSF). A key differentiator for this technology is the ability to analyze hundreds or thousands of samples in a reasonable timeframe (a matter of days or weeks); mass spectrometry-based methods are not scalable to this level of sample throughput for proteomics analyses.

====Protein chips====
Balancing the use of mass spectrometers in proteomics and in medicine is the use of protein micro arrays. The aim behind protein micro arrays is to print thousands of protein detecting features for the interrogation of biological samples. Antibody arrays are an example in which a host of different antibodies are arrayed to detect their respective antigens from a sample of human blood. Another approach is the arraying of multiple protein types for the study of properties like protein-DNA, protein-protein and protein-ligand interactions. Ideally, the functional proteomic arrays would contain the entire complement of the proteins of a given organism. The first version of such arrays consisted of 5000 purified proteins from yeast deposited onto glass microscopic slides. Despite the success of first chip, it was a greater challenge for protein arrays to be implemented. Proteins are inherently much more difficult to work with than DNA. They have a broad dynamic range, are less stable than DNA and their structure is difficult to preserve on glass slides, though they are essential for most assays. The global ICAT technology has striking advantages over protein chip technologies.<ref name="Weston & Hood 2004"/>

====Reverse-phased protein microarrays====
[[File:Mechanism-of-AHA-bonding-to-Amino-Acids.svg|thumb|312x312px|Mechanisms showing how AHA labels onto proteins and where biotin-FLAG-alkyne tags mark the amino acid. Hand Drawn via Sigma Aldrich]]
This is a promising and newer microarray application for the diagnosis, study and treatment of complex diseases such as cancer. The technology merges [[Laser capture microdissection|laser capture microdissection (LCM)]] with micro array technology, to produce reverse-phase protein microarrays. In this type of microarrays, the whole collection of protein themselves are immobilized with the intent of capturing various stages of disease within an individual patient. When used with LCM, reverse phase arrays can monitor the fluctuating state of proteome among different cell population within a small area of human tissue. This is useful for profiling the status of cellular signaling molecules, among a cross-section of tissue that includes both normal and cancerous cells. This approach is useful in monitoring the status of key factors in normal prostate epithelium and invasive prostate cancer tissues.  LCM then dissects these tissue and protein lysates were arrayed onto nitrocellulose slides, which were probed with specific antibodies. This method can track all kinds of molecular events and can compare diseased and healthy tissues within the same patient enabling the development of treatment strategies and diagnosis. The ability to acquire proteomics snapshots of neighboring cell populations, using reverse-phase microarrays in conjunction with LCM has a number of applications beyond the study of tumors. The approach can provide insights into normal physiology and pathology of all the tissues and is invaluable for characterizing developmental processes and anomalies.<ref name="Weston & Hood 2004"/>

=== Protein Detection via Bioorthogonal Chemistry ===
[[File:Ketone-Aldehyde Condensation and Staudinger Ligations.svg|thumb|298x298px|Ketone and aldehyde mechanism with cell surface labeling. Staudinger ligations and their interaction with azide groups for labeling are shown in the second figure.]]
Recent advancements in [[bioorthogonal chemistry]] have revealed applications in protein analysis. The extension of using organic molecules to observe their reaction with proteins reveals extensive methods to tag them. [[Non-proteinogenic amino acids|Unnatural amino acids]] and various [[functional group]]s represent new growing technologies in proteomics.

Specific biomolecules that are capable of being metabolized in cells or tissues are inserted into proteins or glycans. The molecule will have an affinity tag, modifying the protein allowing it to be detected. Azidohomoalanine (AHA) utilizes this affinity tag via incorporation with Met-t-RNA synthetase to incorporate into proteins. This has allowed AHA to assist in determine the identity of newly synthesized proteins created in response to [[Perturbation (biology)|perturbations]] and to identify proteins secreted by cells.<ref>{{cite journal | vauthors = Eichelbaum K, Winter M, Berriel Diaz M, Herzig S, Krijgsveld J | title = Selective enrichment of newly synthesized proteins for quantitative secretome analysis | journal = Nature Biotechnology | volume = 30 | issue = 10 | pages = 984–990 | date = October 2012 | pmid = 23000932 | doi = 10.1038/nbt.2356 | s2cid = 2651429 }}</ref>

Recent studies<ref>{{cite journal | vauthors = Lang K, Chin JW | title = Bioorthogonal reactions for labeling proteins | journal = ACS Chemical Biology | volume = 9 | issue = 1 | pages = 16–20 | date = January 2014 | pmid = 24432752 | doi = 10.1021/cb4009292 }}</ref> using [[ketone]]s and [[aldehyde]]s condensations show that they are best suited for in vitro or [[Proximity labeling|cell surface labeling]]. However, using ketones and aldehydes as bioorthogonal reporters revealed slow kinetics indicating that while effective for labeling, the concentration must be high.

Certain proteins can be detected via their reactivity to [[Azide|azide groups]]. [[Non-proteinogenic amino acids]] can bear azide groups which react with phosphines in [[Staudinger reaction|Staudinger ligations]]. This reaction has already been used to label other biomolecules in living cells and animals.<ref>{{cite journal | vauthors = Devaraj NK | title = The Future of Bioorthogonal Chemistry | journal = ACS Central Science | volume = 4 | issue = 8 | pages = 952–959 | date = August 2018 | pmid = 30159392 | pmc = 6107859 | doi = 10.1021/acscentsci.8b00251 }}</ref>

The bioorthoganal field is expanding and is driving further applications within proteomics. It is worthwhile noting the limitations and benefits. Rapid reactions can create bioconjuctions and create high concentrations with low amounts of reactants. Contrarily slow kinetic reactions like aldehyde and ketone condensation while effective require a high concentration making it cost inefficient.