In 1987, Swiss researchers described two sisters who were born separately but had similar anomalies. There is a circle of tissue in their cerebellum, and there are holes and cracks in the heart. One of them died at the age of three after heart surgery, and her sister had a similar operation at the age of four, but survived. Because the parents of the two girls did not have these abnormalities, the researchers concluded that their daughter inherited two copies of an atypical gene, leading to a previously unknown symptom. Nucleotide abnormalities associated with girl symptoms may be present in a single gene. However, several other genes were subsequently associated with this gene called "Ritscher-Schinzel syndrome." The function of these genes and how they are associated with this syndrome has been a mystery for many years. Today, these molecular foundations have become the focus of attention due to systematic research on protein-protein interactions, a discipline known as the "interaction group." By mapping the network of connections between proteins, the three research groups independently discovered a complex called a "commander" that consisted of proteins produced by mutant genes. The “commander†is an important cellular component that classifies and delivers proteins, and its dysfunction leads to Rischer–Schinzel syndrome with severe defects. In the past three years, the research team has published the first batch of high-quality human interaction omics images. The latest synthesis of these images has identified approximately 93,000 unique protein-protein interactions. It's not easy: capturing all interactions is a challenge because a group of protein partners can change with different tissues, cells, and even time. The interaction group is dynamic and will break or form as the cell responds to the environment. Drawing it completely may require new ways of thinking about systems biology. Despite this, the field is still producing results. Numbers game There are two main ways to construct an interaction set map. The yeast two-hybrid assay tests the interaction between protein pairs by combining gene expression with intracellular protein interactions. The second method maps direct and indirect protein contacts by separating the complexes with antibodies and identifying their components with a mass spectrometer. The laboratory of Edward Marcotte, a system biologist at the University of Texas at Austin, adopted a change based on the second method, which involves biochemically separating proteins (eg, using a sucrose concentration gradient) to observe which molecules tend to stay together. The resulting image allowed Marcotte and his laboratory postdoctoral Anna Mallam to infer the complex cell roles of the “commanderâ€. Those data and other findings suggest that the “commander†will transfer specific proteins from the cell membrane into a space called the Golgi, where they are recycled. At present, the largest map contains thousands of proteins, which are more similar to tangled hair balls than radial starbursts. By unlocking these genes, researchers can identify features that distinguish between oncogenes and "normal" genes, as well as define key biological processes, such as chromosome segregation during cell division. Katja Luck, a computational biology researcher at the Dana-Farber Cancer Institute in Boston, Massachusetts, said that even with multiple methods, the interaction set map is "still incomplete." This is a question about numbers. The human genome contains approximately 20,000 protein-coding genes. If one assumes that each protein has only one form (too simplified), there are about 200 million possible interactions. The actual number may be much smaller because many interactions are indirect and the one-to-one interaction range is estimated to be between 120,000 and 1 million. From a biochemical point of view, the diversity of proteins is incredible, so the interaction between them cannot be captured by every experiment. "We are just beginning to understand the bias of the different methods," Luck said. Gene scissors Luck is a postdoctoral fellow in the laboratory of geneticist Marc Vidal, and the final reference map envisioned by Vidal may contain only a subset of all potential interactions. Changes in cells and tissues and the accumulation of altered cells become many possible versions of all interaction groups. For Matthias Mann, a biochemist at the Max Planck Institute for Biochemistry in Germany, these changes are daunting. But he is optimistic about using the power of gene editing technology, such as using CRISPR-Cas9 to solve these problems. Mann's mapping method involves a library of cell lines expressing hundreds of proteins that are tested by an ultra-high resolution mass spectrometer called an orbitrap. The bait protein is fused to green fluorescent protein to produce a photometric profile that allows researchers to quantify interactions through live cell imaging. In the late first decade of the 21st century, the creation of a cell bank was "very laborious," he said. “Now, thanks to CRISPR genetic engineering technology, our new approach has gained wings.†Since the introduction of this quantification method in 2010, Mann's team has drawn and quantified the strength of more than 28,000 interactions. The interaction of one-to-one ratios of protein pairs is considered "strong" and may exist in stable and abundant complexes. Mann explained that if there is no such information, "it is hard to say what the structure of this network is." An analysis of the maps drawn by his team showed that the human interaction group was dominated by weak associations, which may reflect the effect of low abundance regulatory proteins on more stable protein machinery. Fine adjustment A general trend in this area is the use of relatively mild sample preparation methods aimed at virtually capturing all protein-protein interactions in cells. "We are trying to find a less disruptive approach," said Rosa Viner, biochemist at Thermo Fisher Scientific, a San Jose, California-based life sciences company. The company specializes in improved sample preparation, workflow and mass spectrometry to help researchers identify interactions in cells. “This is the toughest challenge: find ways to get the best photos without any artificial phenomena,†she adds. Artificial phenomena include protein complexes that decompose before their interaction is detected. To bring these complexes together, Viner collaborated with researchers at the University of California, Irvine to chemically fuse complexes prior to mass spectrometry, a method known as cross-linking. A strategy called QMIX (multiplexing of multiplexed, isospecifically labeled cross-linked peptides) has been developed to integrate cross-binding compounds with chemical tags, enabling researchers to stabilize and track proteins. Complex. A good analysis will take into account the blind spots of any given method. "There are still some protein types that are very challenging," says Wade Harper, a cell biologist at Harvard Medical School in Boston. "When doing high-throughput analysis, you're limited to focusing on individual proteins." Each reaction is often treated the same, with little room for customization. Harper and Harvard colleague Steven Gygi created a lab team to tweak their approach. “Our team is relatively small, with only 4 to 6 people, and can create 400 to 500 cell lines per month,†he said. These efforts have so far produced the largest amount of human protein complex data sets through a single channel. Their spectrum is called "bioplex" and contains about 120,000 interactions. Larger picture But in order to take a closer look at these interactions, researchers must delve into the cell's own congestion. Anne-Claude Gingras, a Toronto-based college chemist in Canada, uses a technique called BioID that connects proteins to another protein based on the proximity of the protein. The associated marker protein adds a chemical marker to nearby proteins, leaving evidence of its interaction—like a trace of a toddler waving a room through a room. The result is a physically close neighboring image of the original protein. Gingras explained that identifying a larger community of proteins may reveal details of its cellular function. Close-range imaging also allows researchers to track proteins that cannot be found in other experiments, such as membrane-immobilized proteins that are difficult to separate. Gingras said: "We and other researchers have studied proteins on nuclear chromatin, mapped the tissues of the centrosome, and detected interactions across various membranes." Using BioID, the team found in a signaling pathway. A new component that regulates organ size during development. Lippincott-Schwartz said that this interaction group is a "hypothesis generator" for cell biologists. “Once you see a protein that you know interacts with a bunch of proteins that you don't know its function, you start testing.†As the interaction group images are finally enriched by high quality, rich interactions Researchers will be able to begin to validate those hypotheses. 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