How Spatial Biology Will Change the Future
From neuroscience to agrobiology, spatial biology has the potential to revolutionize cell research
It’s 2040 and you are nervously listening to your immuno-oncologist. “Twenty years ago,” they say, “this type of cancer would have been a death sentence.” They go on to explain how spatial biology technologies allowed them to identify new cell types within tumors like yours. “We are now able to look at the subcellular, biochemical make-up of the individual cells in your tumor.” This technology defined what proteins were present not only in the cancer cells, but it also revealed what proteins were on deck to be made next, based on the transcripts in those same cells.
With relief, you listen to how your doctor will manage the cancer: “With targeted therapies, we can block cancer-specific proteins from being made, so your prognosis is very good. Let me prep your treatment so you can get home.”
What is spatial biology?
Spatial biology looks at individual cells in the context of their 3D environment. This environment includes the cellular neighborhood as well as the extracellular matrix (ECM) that forms the architecture of a tissue.
Spatial biology came into its own as a unique field in the last few years. It is distinct from previous studies due to huge advances combining improved imaging technology with next-generation sequencing. These advances provided the ability to look at proteins and transcripts in single cells, but also subcellular locations of some biomolecules.
By studying spatial biology, scientists can begin to define the space-time situation for molecular expression within individual cells in 3D tissue context. Spatial proteomics looks for the protein expression in individual cells and surrounding ECM, providing an image showing what is happening in the present. Spatial transcriptomics, or the study of RNA transcripts, provides a glimpse of the future for the cell as the RNA transcripts indicate what proteins will be made next.
Spatial biology to help improve our lives
Spatial biology is helping advance fields that can benefit from the ability to look at the 3D architecture of tissues to determine what changes may improve their function.
Rheumatoid arthritis mapping
In 2022, the spatial organization of rheumatoid arthritis (RA) was defined using spatial transcriptomics for the two RA subsets—seropositive and the typically less severe seronegative patients. Going forward, spatial biology techniques will help monitor how patients’ joint tissue and immune systems interact and allow researchers to monitor the disease and analyze responses to treatments.
Drought-tolerance of rice
According to the UN, rice is the most important staple to well over half the world’s population. With global climate change altering the environments rice is grown in, the need to develop drought-tolerant strains is vital. Researchers are using molecular cartography tools to analyze rice roots to understand signal transduction within the xylem of plants that are more drought tolerant than others. These differences may lead to discoveries to improve rice drought tolerance.
Where is spatial biology having an impact?
Sampling and cell culture techniques are limited in their applicability to our understanding of the whole organism. Spatial biology promises to improve that situation. Progress is already being made with spatial biology in immuno-oncology, neuroscience, autoimmune diseases, and agrobiology.
Defining neural cells
Researchers are using spatial biology to tease out what happens in context, in damaged tissues of Alzheimer’s patients compared to normal brain tissue. One of the most recent advances is the characterization of disease-associated microglial cells in these patients. Paul Steinberg, chief commercial officer of Resolve Biosciences, describes microglia as the vacuum cleaners of the brain, but in Alzheimer’s patients, “these diseased microglia are misfiring somehow.” These results wouldn’t have been possible without the ability to define the subsets of microglia using multiple markers and single-cell analyses. “We've recently found out that it's not actually the plaques that are causing the disease…the plaques are just a function of the disease,” explains Steinberg. Further study with spatial biology techniques may finally identify what causes Alzheimer’s disease.
Many genomic and proteomic changes that define cancer cells have been teased out with traditional techniques. These protocols rely on dissolving tissues, or cell culture studies, which are removed from tissue context altogether.
Tumors are a complex combination of cancer cells, immune cells, ECM, and many types of healthy host cells. Spatial biology is beginning to show how complex a tumor can be. It is defining multiple microenvironments within a tumor, each with their own variety of cancer cells and variations in the host’s response. Steinberg explains some of the questions spatial biology studies will hopefully answer: “You want to know, is the immune system being recruited to the tumor? Is it recognizing it through the signals? Are there certain parts of the tumor that it's being recruited to, and other parts that are being ignored, that could cause remission or a recurrence?” Answers to these questions will help guide what targets for therapy could be.
Limitations and challenges of spatial biology
The rapid development of spatial biology tools is also causing some of its biggest challenges. Because spatial biology is a cross-disciplinary technology, the number of researchers that have the requisite knowledge in the different fields is currently small. There is a need for training and education of users in the various aspects of the field.
The problem with the lack of skills is compounded by the related lack of best practices. With any brand-new technology, the results coming in from many different groups can’t necessarily be compared, because each group has developed their own protocols. The fields in spatial biology will need to develop best practices to be able to compare results and ensure reproducibility.
Other challenges are more technical:
• Sensitivity of visualization continues to challenge researchers, especially as they strive to look at very rare transcripts.
• Tissue thickness still limits visualization of tissue architecture in 3D in part due to tissue autofluorescence.
• Preknowledge is currently needed for certain experimental designs. Shotgun approaches to look for unknown targets is difficult in proteomics because antibodies must be made and selected for known proteins.
• Multiplexing is one of spatial biology’s great strengths, but it is still limited to about 20 markers.
• Tissue handling, extraction, and preservation techniques are typically incompatible between the difference omics, making multi-omics studies difficult on the same samples.
The future of spatial biology
Looking at the challenges, you can see where the most progress is likely to happen. Tissue sampling techniques, protocols, and even kits will be needed to facilitate multi-omics approaches so a single sample can be used. Although transcriptomics and proteomics are the foundations of spatial biology, the same approaches will be useful with other omics, such as metabolomics or lipidomics, to define tissue, cellular, and subcellular architectures.
As artificial intelligence (AI) improves, it will help reduce bias in spatial biology. It can also quickly analyze the whole slide instead of just a particular field of view, as well as look for correlations missed by the human eye. AI and computer learning will also help process and integrate the terabytes of data produced by even a single image. Computer advances will also help generate 3D models from 2D slices.
Finally, it is expected that imaging technology will continue evolving as it has in recent years. Improvements are being developed to enhance depth of images for thicker slices, and sensitivity to define both subcellular locations of molecules, but also rare transcripts. Other revolutionary digital advances are the huge numbers of omics databases and mapping resources becoming available.
Spatial biology offers great hope that by 2040, we can indeed expect advances in identification and treatment options for many diseases and other human biological challenges.