A new map reveals a complicated world where cells are trying to repair

Writing in the May 22, 2023 issue Cell Systema diverse team of scientists, led by researchers at the University of California San Diego School of Medicine, have produced a new map depicting the human body’s incredibly complex and highly evolved system for coping with and repairing DNA damage—the cause and effect of many diseases.

DNA damage and replication errors caused by stress and other factors play a major role in disease, and are hallmarks of cancer and other afflictions. To maintain genome integrity and support normal function and health, cells have developed intricate networks of cell cycle checkpoints and DNA damage repair tools, collectively known as the DNA damage response or DDR.

Defects in DDR are linked to many diseases, including cancer and inherited neurological disorders caused by unstable DNA, repeat errors, rearrangements, and mutations. On the other hand, a better understanding of how DDR works and why it sometimes fails provides new therapeutic opportunities for treating or curing the same disease.

“An ongoing challenge, of course, is that DDR is a very complex system involving hundreds of different proteins that are assembled in different ways to address different problems,” said senior author Trey Ideker, PhD, professor at UC San Diego School of Medicine and UC San Diego Moores Cancer Center. “You can’t fix problems with DDR until you understand how it works.”

In the new paper, Ideker and colleagues take a major step forward in elucidating the complexity and function of DDR, generating a multi-scale map of protein assembly in DDR.

Unlike previous maps, based on published scientific literature that included conflicting findings or tended to focus only on well-studied mechanisms, the new reference map uses affinity purification mass spectrometry and broad multi-omics datasets to develop a more complete picture: hierarchies organization of 605 proteins in 109 assemblies that capture canonical repair mechanisms and propose new DDR-related proteins related to stress, transport, and chromatin functions in cells.

Multi-omics is a new approach in which data sets from different omics groups are combined during analysis to create a more complete and nuanced understanding of whole systems and organisms.

The cell contains various classes of molecular processes: genomics, transcriptomics, proteomics, and others. Each of these molecular “omics” processes involves interactions between thousands of genes, transcripts, or proteins. To understand this complexity, scientists tend to take a reductionist view, examining the omics one by one.

In contrast, systems biology considers molecular processes simultaneously and holistically, using machine learning and other tools to evaluate the extent to which different molecular processes inform each specific interaction, and how overall systems and networks work. Machine learning describes computer systems that are capable of learning and adapting without following explicit instructions. This is an artificial intelligence application.

Experimental screens of increasing scale capture interactions between genes or proteins in human cells, often beyond what has been described in the literature. In principle, they could be used to create data-driven DDR maps,” said first author Anton Kratz, PhD, a former research scientist in Ideker’s lab who now works at The System Biology Institute in Tokyo, Japan.

But screening presents its own challenges because different shapes can measure molecular processes separately, missing some of the interactions that only occur under certain stresses or conditions. To address this challenge, the researchers measured a novel protein-protein interaction network centered around 21 key factors of DDR with and without DNA damage. They developed a machine learning approach to combine the new data with existing data, and the statistical analysis that shows the results significantly informs the resulting maps.

“For me, two things were most telling,” says Kratz. “Firstly, there are lots of new proteins on the map. Approximately 50% of the proteins included in the map following our data-driven paradigm were not included in the literature-curated maps considered here, justifying a data-driven approach to map building.

“Second and related, DDR membership is not a binary affair, but occurs on a continuum (and we measured this continuum), extending to stress, transport, and chromatin functions.”

Researchers have created interactive software that will allow other scientists to investigate DDR proteins and interactions with special interest. Kratz said scientists could also use maps as components in visible machine learning systems that could potentially shed light on bigger questions, such as how DDR is relevant in the transition from genotype (genetic constitution of an individual organism) to phenotype (characteristics of an individual). resulting from the interaction of its genotype with the environment). For example, how exposure to drugs or toxins can change DDR.

Co-authors include: Minkyu Kim, Maya Modak and Nevan J. Krogan, UC San Francisco; Mark Kelly, Fan Zheng, Keiichiro Ono, Yue Qin, Christopher Churas, Jing Chen, Rudolph T. Pillich, Jisoo Park, Rachel Collier, Kate Licon and Dexter Pratt; Christopher A. Koczor, Jianfeng Li, University of South Alabama; Robert W. Sobol, Brown University.

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