New Spaceomics Techniques: Exploring the Early Stages of Disease

Most illnesses are initially asymptomatic, and the affected person usually still feels good — symptoms haven't yet appeared, or are still too mild to be aware of
.
However, changes have taken place inside the body: the virus may have begun to replicate, or a rogue cell may be dividing more often
than normal.
But how can these changes be detected? How do you find a diseased cell in a tissue or organ? The search is like finding a needle
in a haystack.
Researchers face a similar dilemma
when studying the early development of the disease.
Even when using animal models, scientists struggle to identify small sites of disease onset or describe the exact molecular changes
that drive disease progression.

Spatial molecular profiling of complex tissues is essential
for studying cellular function in physiological and pathological states.
Existing spatial group expression profiling for tissue sections has brought rich information to the study of disease mechanisms, however, molecular analysis methods
for three-dimensional imaging of large biological specimens are currently lacking.

The team of Ali Ertürk from the University of Munich in Germany and Matthias Mann from the Max Planck Institute for Biochemistry have now developed a new technique called DISCO-MS that combines transparent imaging of mouse or human tissue/whole organs, deep learning-based image analysis, robotic tissue extraction and ultra-high sensitivity mass spectrometry proteomics techniques to obtain proteomic data from "diseased" cells that are precisely identified early in the disease This helps researchers to delve deeper into the molecular changes
at the onset of disease.

DISCO-MS: Transparent detection of early molecular changes

DISCO-MS first performs DISCO tissue clearing, making mouse bodies or human organs transparent, making them easy to image.

Thus, fluorescently labeled cells can be easily identified at specific sites of intact tissue using high-resolution 3D microscopy
.

Once the region of interest was identified, they used a novel robotic technique called DISCO-bot for separation, in which robot-assisted extracted tissue was analyzed using advanced mass spectrometry (MS) methods, a high-tech method that allows the complete molecular signature
of any desired tissue region to be identified in 3D throughout the mouse body or human organs.

• DISCO-MS is an optically transparent whole-sample spatial proteomics technique
• DISCO-MS obtains proteomes
similar to fresh samples with the aid of artificial intelligence and robotics • DISCO-bot-assisted DISCO-MS reveals spatial immune cell heterogeneity in mouse bones, as well as heterogeneity in human coronary plaque

Early detection can detect diseases

To demonstrate the power of the method, first author Harsharan Singh Bhatia and colleagues applied DISCO-MS to atherosclerotic plaques (pathological sclerosis and narrowing of blood vessels) in mouse models of Alzheimer's disease (AD)
and human hearts.
In tissue samples from the AD model, the team applied artificial intelligence (AI) to identify typical AD plaques in the early stages of
the disease, which are difficult to detect by any other method.
Subsequent proteomic analysis of plaques provides an unbiased and large-scale study of proteins affected by AD, revealing new molecules
that may be Alzheimer's disease biomarkers.

In the human heart, researchers are interested in the composition of the tissue surrounding atherosclerotic plaques, which can be seen
soon after the tissue is cleared.
Artificial intelligence detection and robotic extraction of tissue again allow the identification of dysregulated molecular pathways
in human heart cells associated with aortic plaque.
These results are key findings as they form the basis of
potential therapeutic targets.

conclusion

DISCO-MS is the first complete 3D spatial omics technique to obtain proteome data
in rodent and human tissues that were indistinguishable by previous methods.
The authors used DISCO-MS to study microglial activation along the axonal bundle after brain injury and characterize
amyloid plaques in early and late individuals β Alzheimer's disease in mouse models.
DISCO-bot robotic sample extraction allowed the researchers to study regional heterogeneity
of immune cells and aortic plaques in intact human hearts in intact mice.
DISCO-MS enables unbiased proteome analysis of preclinical and clinical tissues following 3D unbiased imaging of entire specimens to identify diagnostic and therapeutic opportunities for complex diseases, accelerating research on complex diseases
ranging from cancer to metabolic disorders.
Because DISCO-MS collaborates with preclinical and clinical organizations, it is able to conduct studies in the early stages of the disease and subsequently develop potential new therapies
.

Journal Reference:

1. Harsharan Singh Bhatia, Andreas-David Brunner, Furkan Ö ztü rk, Saketh Kapoor, Zhouyi Rong, Hongcheng Mai, Marvin Thielert, Mayar Ali, Rami Al-Maskari, Johannes Christian Paetzold, Florian Kofler, Mihail Ivilinov Todorov, Muge Molbay, Zeynep Ilgin Kolabas, Moritz Negwer, Luciano Hoeher, Hanno Steinke, Alina Dima, Basavdatta Gupta, Doris Kaltenecker, Ö zü m Sehnaz Caliskan, Daniel Brandt, Natalie Krahmer, Stephan Mü ller, Stefan Frieder Lichtenthaler, Farida Hellal, Ingo Bechmann, Bjoern Menze, Fabian Theis, Matthias Mann, Ali Ertü rk.
   Spatial proteomics in three-dimensional intact specimens.
   Cell, 2022; 185 (26): 5040 DOI: 10.
   1016/j.
   cell.
   2022.
   11.
   021