PMLS 2023 Insights: Combining Technological Advancements for Improving Human Health
The technological advancements that we have witnessed in biotechnology in the last 20 years have been incredible. After sequencing the first few genomes, fast forward to current days and initiatives such as Tabula Sapiens and the Human BioMolecular Atlas Program with goals to atlas all healthy cells in the human body and understand how they interact in the same tissue. It is mind-blowing. In face of such advancement and incredible research, one wonders how all of these technological advancements and knowledge is ready to be applied to improve human health. This was the exact topic of discussion during the Precision Medicine Leader’s Summit (PMLS) hosted by GenomeWeb September 14-15, 2023 in San Diego. The aim of this inspiring conference was to examine the advances in single cell and spatial biology that will progress the future of precision medicine. There was a combination of exciting insights on how these technologies can be combined to further understand the biology of unique human diseases as well as the realization of the big challenges ahead for wide adoption. Academia, pharma and technology developers were all together and openly sharing the vision and roadblocks. This post summarizes the discussions captured during the meeting and how Levitation Technology is part of the solution – I hope you find it enlightening! The vision Beyond the beautiful images that are generated, there is a lot of excitement with spatial analysis. It is clear that identifying the expression and location of expressed RNA and protein in a tissue sample helps characterize and understand some of the mechanisms of disease development. But how can that can be leveraged in practice? A speaker from Providence Genomics shared the vision for how spatial can be utilized for routine molecular pathology for automated high-throughput marker screening. Artificial Intelligence (AI) tools would cross-check results from spatial analysis with clinical trial databases to inform new possibilities of treatments given the transcriptional and protein profile of the sample – fully automated precision medicine! Speakers from The Pittsburgh Foundation in Precision Medicine and St Jude Children’s Research Hospital enlightened the audience with use cases of how the combined analysis of single-cell RNA sequencing (scRNA-seq) and spatial data can benefit specific human conditions. In aggressive breast cancer subtypes and some mental disorders, the biomarkers detected with scRNA-seq do not change between affected vs non-affected. However, through spatial analysis it is observed that their location changes, inviting researchers to think about a completely different angle when deciphering disease mechanisms and, therefore, potential new treatments. Where we stand Each presenter instilled excitement with a dose of reality. There are many challenges to be overcome to apply these technologies to human health. The list is not that long but the considerable effort will take the engagement of the full scientific community. Given that single-cell analysis adoption penetrates the community’s early majority (34% of market share) and spatial adoption is mostly with innovators (2.5% of market share) the challenges faced are different and thus, split below. Single-Cell Analysis Challenges 1. Inaccessible samples: relevant tissue samples require processing into single-cell suspensions. Typical methods for sample processing may result in cell stress causing biased cell subtype death and absence from scRNA-seq datasets. This causes a misrepresentation of biology, steering scientists towards incomplete or wrong conclusions. Levitation Technology is uniquely positioned in the market by processing samples for dead cells and debris removal in parallel to cell subtype enrichment with a gentle method that preserves cells’ native state. Review how the LeviCell® systems have allowed research in fragile samples such as brain metastasis and intestinal biopsies in these webinars: 2. Cost of instrumentation and sequencing reagents: the trend highlighted during the conference by the DeciBio team is that technology manufacturers are responding quickly to this need. Box-less or instrument-free options for scRNA-seq library preparation are getting ahead of the curve, delivering to specific needs identified as gaps from the market leader. On the same topic of preserving the full biology of samples, ParseBio showed how their method improved the detection of the number of genes and fragile cell subtypes as compared to 10x Genomics. Singular Genomics also shared that for an equivalent data quality as the market leader Illumina, you can get flexibility in sequencing depth with each run, helping researchers decrease the cost of optimizing new assays. 3. Difficulty in scaling: this is a complex challenge, touching upon different aspects of scaling. Spatial Analysis Challenges Interestingly, cost and workflow complexity were not mentioned as challenges for spatial analysis. The excitement of what can be achieved with spatial is taking priority and the challenges appreciated are forward-looking, assuming that the relevance of spatial analysis to human health application is a given. It surely looks that way! The race between technologies – will there be a winner? It was clear from the DeciBio’s team that single-cell analysis will continue co-existing with spatial. However, users anticipate allocating up to 60% of their single-cell analysis budget to spatial in the next 5 years. A speaker from Memorial Sloan Kettering Cancer Center shared his results from a comparison of 5 different methods of sample quality improvement prior to scRNA-seq using fragile samples. Each method has its benefits and disadvantages. The LeviCell EOS system showed a superior ability to preserve the highest percentage of the most fragile cell subtypes in the scRNA-seq dataset from samples derived from mouse cerebrospinal fluid and lymph nodes. Additionally, the speaker reminded us that in the end, the technology applied does not matter as much as answering the scientific questions at hand. It is all about having a varied set of tools in your toolbox! Check out this webinar with interesting insights about how to best utilize single-cell tools to investigate different biological questions in a webinar produced by LevitasBio in collaboration with Dr Ronan Chaligne, Head of the Single-cell Analytics Innovation Lab (SAIL) at Memorial Sloan Kettering Cancer Center, here.
Single-Cell Analysis – 3 Pitfalls All Researchers Face
Single-cell analysis has become a key driver of scientific discovery. The move from studying populations of cells to studying single-cells has powered a more detailed and accurate understanding of cellular processes – and fueled numerous advances in immunology, oncology, and neuroscience. However, there are 3 pitfalls to single-cell analysis that can lead to incorrect biological conclusions, stalled research, and wasted resources – a true research nightmare. 1. Samples with low viability can lead to wasted sequencing reads and fewer cells sequenced2. Samples with low cell numbers may result in unusable data3. Samples with excess dead cells and contaminants can produce data that is not statistically [or bioinformatically] sound, adversely affecting your findings
Reduce the Garbage in Your scRNA-seq Data
Reduce the Garbage (aka Noise) in Your scRNA-seq Data to Ensure Meaningful Data Single-cell transcriptional data sets can illuminate the path to that rare, elusive cell type lurking in the shadows, undiscovered by bulk sequencing, waiting to stand in the spotlight. To optimize the return of unique phenotypic signatures, it is important to start with a healthy cell population free of dead cells and residual debris. Unfortunately, some of the most interesting problems require tissues that contain notoriously high amounts of these contaminates, such as solid tumors, brain tissue, or any research samples that must be cryopreserved before processing. Given that library preparation costs tend to be fixed, getting the best return on your investment means maximizing the number of usable cells and reducing the noise. In other words, steering clear of the old adage, “garbage in, garbage out.” Since apoptotic cells, dead cells, and residual ambient RNA can all make their way into single-cell sequencing data sets, the raw data is screened via a set of standard QC metrics to help filter these contaminants out before proceeding to downstream analyses. In this latest Research Snapshot, we have evaluated some of these quality control (QC) metrics in a single-cell data set from whole mouse brain that has undergone both viable cell enrichment on the LeviCellTM system as well as no enrichment. We demonstrate that enrichment using Levitation Technology elevates the single-cell suspension by increasing the ratio of viable cells to dead cells and debris, improving the quality of the data set across a total of eight recommended QC parameters. Higher quality data means more usable information, which ultimately can lead to more accurate and reproducible discoveries. >> Download Research Snapshot
Optimization of a Tissue Dissociation Workflow for Single Cell Analysis
New Tissue Dissociation Workflow for Single Cell Analysis The complexity of dissociating complex tissue into single cells Isolating cells for cancer diagnostics is critical if personalized medicine is to flourish. However, dissociating complex tissues into single cells while maintaining cellular integrity and stable genetic expression is poorly understood and most present approaches in the lab do not have the efficiency that is needed to be clinically relevant for processing of samples of heterogeneous tissue. A new approach: 15 minute chemical-mechanical dissociation protocol Writing in a recent issue of Cellular and Molecular Bioengineering, (Vol. 14, No. 3, June 2021 pp. 241–258; https://doi.org/10.1007/s12195-021-00667-y) researchers from the Center for Biomedical Engineering at Brown University reveal a 15 minute chemical-mechanical dissociation protocol for clinically relevant preparation of single-cell suspensions from frozen biopsy cores of complex tissues. Dissociation and analysis of frozen bovine liver biopsy cores Frozen bovine liver biopsy cores were normalized by weight, dimension, and calculated cellular composition. Various chemical reagents were tested for their capability to dissociate the tissue via confocal microscopy, hemocytometry and quantitative flow cytometry. Images were processed using ImageJ. Quantitative flow cytometry with gating analysis was also used for the analysis of dissociation. Physical modeling simulations were conducted in COMSOL Multiphysics. The researchers established that a combination of 1% type-1 collagenase and pronase or hyaluronidase in 100 U/lL HBSS solution is the most effective at dissociating 2.5 mm thawed bovine liver biopsy cores in 15 min, with dissociation efficiency of 37-42% and viability >90% as verified using live MDA-MB-231 cancer cells. Cellular dissociation is significantly improved by adding a controlled mechanical force during the chemical process, to dissociate 93 + 8% of the entire tissue into single cells. The protocol demonstrates that controlled mechanical force in combination with chemical treatment produces high quality tissue dissociation. Applicability to different tissue and cell types According to the researchers, the applicability of this workflow is likely to hold for most soft tissues, which are the tissue type that is most frequently dissociated in practice. However, the success of this protocol across different tissue and cell types, especially fibrous, crosslinked, and necrotic or diseased tissues, should be investigated further.