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1. Briefly explain SWATH-MS, and how is it beneficial in better detection of protein constituents in clinical samples.

If the proteins are present in the disease patient but not in the healthy patient, from there we can develop a disease biomarker.

SWATH-MS is based on DIA, swath will gave u same result even after the repition of the experiment even after 100 times.

It’s useful because it gives you 100% of the protein content that you have in your sample without missing anything. Because it fragment reinterrogate and ionizes each one of these fragments social against integrated databases and it gives what exactly was in the sample. So its maximizes the pool of the protein aassociating with the diseases as suppose be the healthy cell which means it maxmizes the pool of biomarker that can so we can work upon to discover discover to target these proteins or interaction network. 

· Data independent acquisition (DIA) via SWATH considers all possible theoretical fragment ion spectra as a starting point and, reversibly concludes parent ions. In SWATH-MS, protein samples are digested with trypsin, and the collection of digested peptides is subsequently analyzed in a DIA mode, where all ionized peptides within a certain mass range are fragmented using overlapping windows of ~25 m/z each, thus enabling re-interrogation of data upon improving detection capabilities that expands the list of identified proteins in various clinical samples.

· –  This is unlike the case with information-dependent acquisition, where low protein abundance data are lost permanently. SWATH-MS style of re-examining co-fragmentation patterns of the co-eluting peptides creates a digital biobank for each sample and offers orders of magnitude increase in large-scale quantitative proteomics with great precision, while addressing data reproducibility concerns. This qualifies SWATH-MS as a high-throughput quantitative proteomics tool that can be of particular value in biomarker discovery.

· –  In fact, almost half of SWATH-MS applications were applied to the area of clinical proteomics and biomarker discovery research. Unlike classical selected or multiple reaction monitoring approaches, SWATH-MS is more useful in biomarker discovery attempts such as the case with nasopharyngeal carcinoma, where carbonic anhydrase 2 was identified as a reliable biomarker for this rare cancer type. On the brain disease front, differential expression of the presynaptic mt proteome at various developmental stages of neuronal synapses has been achieved as a proof of concept.

· –  In addition, secretome profiling in rare cancer types, such as pancreatic cancer, can be achieved by SWATH-MS, which was applied for differential secretome mapping between two variants of the TP53 transcriptional regulator to fine-tune variant-specific biomarker discovery outputs.

– Another important yet significantly understudied area of clinical research is metabolomics and their linkage to human disease. A comparative profiling study of both human serum and plasma using SWATH-MS showed subtle variations in proteomic profiles between these samples but revealed significant metabolomic differences, which sheds light on how sample handling and storage can impact blood metabolome profiles, thereby questioning the reliability of putative disease biomarkers.

– More recently, patient saliva is becoming one of the most attractive body fluids to collect and analyze as patient-convenient and a non-invasive approach in disease diagnostics. However, the quality of sample preparation can drastically impact positive testing outcomes, and SWATH-MS is being gradually applied as the method of choice to assess saliva sample preparation quality.

2. What is the powerful advantage of QUBIC-based triple interactome mapping in detecting low abundance or transient protein-protein interactions?

– Quantitative bacterial artificial chromosome (BAC)-green fluorescent protein (GFP) interactomics (QUBIC) has been attempted for human interactome mapping that captures low-abundance and transient PPIs with great efficiency. Two factors play a critical role in interactome mapping: strength of interactions and the abundance of interacting proteins, both of which can impact the output based on the mapping method used. Thus, interaction networks are the collective result of binary affinities and cellular distributions of all proteins.

– QUBIC has been implemented to offer three quantitative interactome dimensions: detecting specific interactions via local co-enrichment profiles, interaction stoichiometries, and cellular abundance of the interacting proteins, which can uncover weak interactions in orders of magnitude when compared with established methods. The QUBIC approach led to the discovery that the human interactome is dominated by weak and transient PPIs, which can be suitable to study dynamic changes in organelles such as the mt.

– BACs are large bacterial chromosomes ranging from 150 to 300 kb that can accommodate large mammalian genes, along with their regulatory elements. BACs are engineered to clone mammalian genes of interest, along with their cognate promoter, intron-exon make up and regulatory elements, while tagging the protein product with GFP. BACs propagate independently of the E. coli chromosome; thus they can be purified and transfected into HeLa cells and the GFP tag is used for dual purpose: imaging and AP/immunoprecipitation (IP) followed by MS. A total of 1,125 mice orthologs of the human counterparts were cloned on BACs as N- or C-terminal GFP-tagged baits and expressed as transgenic fusions in HeLa cells to map human interactomes spanning all protein classes.

3. Explain how imaging MS/PLIC is implicated in detecting and characterizing low abundance protein-protein interactions.

A newly developed approach termed proximity ligation imaging cytometry (PLIC) offers promise to advance low abundance proteomics. This method has been demonstrated through a proof of concept in medullary thymic epithelial cells (meTECs). Single cell suspensions of thymi were prepared from fat-free surgically removed thymi from 5-week-old mice, followed by enzymatic and mechanical treatment to create a suspension of single cells for PLIC analysis.

– PLIC essentially combines nucleotide-based proximity ligation assay (PLA) with imaging flow cytometry (IFC). It conceptually relies on targeting the protein of interest with an oligonucleotide-conjugated antibody. If another protein is targeted with a second oligonucleotide-conjugated antibody and both proteins interact, the two oligonucleotides get into proximity, prompting the ligation of additional connector DNA strands and yielding a circular DNA, the product of which can be detected by fluorescence microscopy.

PLIC can also be used to quantify dimerization and oligomerization states of individual proteins by targeting the same protein in any cell type with two different oligonucleotide-labeled antibodies, and if the protein dimerizes or oligomerizes, the outcome will yield fluorescent signals that can offer insights into interaction stoichiometries.

PLIC offers additional importance in PTM analysis of diseases by probing for the protein of interest with two different unlabeled primary antibodies that target select protein and its modified molecule, respectively, such as lysine-acetylation specific antibody.

PLIC thus offers a significant push to PPI (protein protein interactions )and PTM (post-translational modifications) research, especially in rare cell types. For example, numerous mitochondrial respiratory chain proteins that are involved in the assembly of complexes I–IV are phosphorylated under healthy conditions, resulting in increased or decreased activity. In diseases such as RCC deficiency, PLIC can be the method of choice in monitoring the fluorescence signal patterns in response to fluctuations in PTMs of special complex subunits of interest, when compared with healthy subject signals, thus offering a new dimension into the impact of PTM alterations in human disease.

4. Explain crosslinking mass spectrometry (XL-MS). Outline one useful application of XL-MS in biomarker discovery.

 Cross linking mass spectrometry is a high throughput tool for studying proteins. It analyses protein protein interactions that are locked in a place to better understand how protein affects the biological processes.

Application of mass spectrometry in biomarker discovery – 

In biomarker discovery mass spectrometry plays a major role in identifying and quantifying proteins from accessible complex mixture like plasma. It helps in identifying relevant biomarkers for disease progression and assessing the organism response to treatment with better outcomes for patients.

Crosslinking mass spectrometry (XL-MS) analyzes protein-protein interactions that are “locked in place” to better understand how proteins affect biological processes such as signaling cascades, gene upregulation, and energy (ATP) production.

Crosslinking mass spectrometry has emerged as a powerful technique for examining protein-protein interaction.

The first step is selecting a crosslinker and reacting them with proteins. crosslinker can link groups on the same protein (intraprotein) or different proteins (inter-protein). An example of intra protein is linking the amine group of N Terminus and mine with a side chain of Lysine in the same protein.While inter protein  is linking the side chain of Lysine in one protein with another lysine from a different protein.  

Thereafter the proteins are digested giving crossed the ink and linear peptide Through gel filtration  chromatography the linear peptides are filtered out and the Crosslink Pop-Tarts are put through Mass spectrometry. The sample is passed through and vision chamber and accelerated lighter ions and ions with charges greater than + 1 are defected more this is detected and Mass Spectrum is generated.

the Mass Spectrum is searched against aT database. he more the experiment the more reproducibility and quality interactions are obtained. 

Application- this method can be used to find the protein protein interactions in tissues from healthy people and patients. if certain protein-protein interactions are found in patient tissue and nowhere in the healthy tissue then those PPIs  can act as biomarkers for an unknown disease.  targeted proteomics can then be performed which help in diagnosis and therapeutic discovery.