TBI is a growing public health concern, affecting more than 1.7 million Americans at an estimated annual cost of $76.5 billion dollars. It is a leading cause of death and disability for children and young adults in industrialized countries, and people who experience TBI are more likely to develop severe, long-term cognitive and behavioral deficits.
“Unfortunately, the molecular and cellular mechanisms of TBI injury progression are multifaceted and have yet to be fully elucidated,” said Sarah Stabenfeldt, an ASU professor and the leader and corresponding author of the study, which appears in the journal Science Advances.
Their research approach was to perform a “biopanning” search to reveal several key molecular signatures, called biomarkers, identified directly after immediately after the injury event (the acute phase), and also the long-term consequences (the chronic phase) of TBI.
“For TBI, the pathology evolves and changes over time, meaning that a single protein or receptor may be upregulated at one phase of the injury, but not two weeks later,” said Sarah Stabenfeldt. “This dynamic environment makes developing a successful targeting strategy complicated.”
To overcome these limitations, The ASU scientists, led by Sarah Stabenfeldt utilize a mouse model for their study to begin to study the root causes of TBI by identifying biomarkers—-unique molecular fingerprints found with a given injury or disease.
“Using the established mouse model enabled us to conduct biomarker discover where the complexity and evolution of the injury pathology was progressing.”
Scientists can often begin to design therapeutic agents or diagnostic devices based on biomarker discovery. Stabenfeldt’s team used a “bottom up” approach to biomarker discovery.
“Top-down” discovery methods are focused on assessing candidate biomarkers based on their known involvement in the condition of interest,” said study first author Briana, a recent Ph.D. graduate in Stabenfeldt’s lab.
“In contrast, a “bottom-up” method analyzes changes in tissue composition and finds a way to connect those changes to the condition. It’s a more unbiased approach but can be risky because you can possibly identify markers that are not specific to the condition or pathology of interest.”
Next, they utilized several state-of-the-art ‘biopanning’ tools and techniques to identify and capture molecules, including such a “bait” technique for fishing out potential target molecules called a phage-display system, in addition to high-speed DNA sequencing to identify protein targets within the genome, and mass-spectrometers to sequence the peptide fragments from the phase display experiments.
“The blood-brain barrier (BBB) barrier is a barrier between the vascular and brain tissue,” explains Stabenfeldt. “In a healthy individual, the BBB tightly regulates nutrient and waste exchange from the blood to the brain and vice versa, essentially compartmentalizing the brain/central nervous system.”
A dAb phage parent library was produced and purified and then intravenously injected into a mouse that sustained a controlled cortical impact (CCI) at a distinct time point (1, 7, or 21 dpi) or a sham injury (sacrificed 1 day post-procedure). Tissues were extracted, lysed, and trypsinized to cleave phage from tissue. The phage library from the ipsilateral hemisphere was then amplified with TG1 E. coli and applied in the final round of biopanning. Recovered phages were then analyzed using NGS.
‘However, this barrier also complicates drug delivery to the brain so that most molecules/drugs do not passively cross this barrier; therefore, the drug delivery field has sought out ways to modulate both entry and delivery mechanisms. Similarly, for blood-based biomarkers for TBI or other neurodegenerative diseases, specificity to the pathology and transfer of the molecule (if it originates in the brain) from the brain to blood is a challenge.”
When a TBI occurs, the initial injury can disrupt the BBB, which triggers a cascade of cell death, torn, disrupted tissues and debris.
The long-term injury causes inflammation and swelling, and results in the immune response to spring into action, but also can lead to an impairment of the brain’s energy sources, or can choke off the brain’s blood supply, leading to more neuronal cell death and permanent disability.
A key advantage of their suite of experimental tools and techniques of the phage display system is that the molecules and potential biomarkers identified are small enough to slip through the tiny holes within the meshwork of the BBB— thus, opening the way to therapeutics based on these molecules.
So, despite all these obstacles, the team found a way.
“Our study leverages the sensitivity and specificity of phage to discover novel targeting motifs,” said Stabenfeldt. “The combination of phage and NGS [next-generation sequencing] has been used previously, thereby leveraging bioinformatic analysis. The unique contribution of our study is putting all of these tools together specifically for an in vivo model of TBI.”
They found a suite of unique biomarkers associated with only the acute or chronic phases of TBI. In the acute phase, TBI targeting motif recognized targets associated with mainly metabolic and mitochondrial (the powerhouse of the cell) dysfunction, whereas, the chronic TBI motif was largely associated with neurodegenerative processes.
“Our method for biomarker discovery was sensitive enough to detect injury in brains that were collected at different points in the experiments,” said study first author Briana Martinez, a recent Ph.D. graduate in Stabenfeldt’s lab.
“It was really interesting to see that proteins involved in neurodegenerative diseases were detected at 7 days post-injury, but not at the earlier, 1-day post-injury timepoint. The fact that we were able to observe these differences really showcases how useful this method could be in exploring various aspects of brain injury.”
It may also begin to explain why people who have had a TBI are more susceptible to developing neurodegenerative diseases like Parkinson’s and Alzheimer’s later in life.
This successful discovery pipeline will now serve as the foundation for the next-generation targeted TBI therapeutics and diagnostics.
Next, the group plans to further its collaborations with ASU’s clinical partners and expand their studies to begin to look for these same molecules in human samples.
Traumatic brain injury (TBI) is currently a substantial public health problem and one of the leading causes of morbidity and mortality worldwide (Dewan et al., 2018). However, the transcriptional changes after TBI at single-cell level have not been well characterized.
In this study, we identified 10 cell types, including astrocytes, endothelial cell, ependymal cell, excitatory neuron, fibroblast-like cell, inhibitory neuron, microglia, mural, OPCs, and oligodendrocyte utilizing scRNA-seq data. Among these cell types, oligodendrocyte accounted for the highest proportion of total cells, which was consistent with the observation that oligodendrocytes proved to be the most abundant glial cells in the mouse brain in a previous study (Valério-Gomes et al., 2018). The sub-clustering analysis identified three oligodendrocyte subpopulations (C0-C2), that were characterized by apoptotic, differentiated, and intermediate early states, respectively. The trajectory analysis also indicated that the oligodendrocytes might develop from C2 to C1, eventually to C0. In this study, we calculated the cell proportions for each sample and compared the cell proportions between TBI and Sham groups using t test, and our findings were inconsistent with the previous scRNA-seq study where both oligodendrocytes and OPCs were significantly decreased post-TBI (Arneson et al., 2018).
The differential cell proportion analysis revealed that astrocyte populations were significantly expanded in TBI samples. Moreover, the astrocytes were activated in TBI, as Gfap, a marker of astrocyte activation and a hallmark of multiple central nervous system (CNS) pathologies (Sofroniew, 2009), was significantly upregulated in TBI. Moreover, inflammatory response-related pathways, including signaling by interleukins, IL-18 signaling pathway, and interleukin-4 and interleukin-13 signaling pathways were significantly upregulated in the astrocytes in TBI samples. As microglia were well-recognized as major resident immune cells of the brain (Ginhoux et al., 2013), we also investigated their transcriptional changes after TBI. Consistently, inflammatory pathways such as IL18 signaling pathway, neutrophil degranulation, chemokine receptor bind chemokines, NOD-like receptor signaling pathway, and TYROBP causal network were highly enriched by those upregulated genes in the microglia in TBI samples (Supplementary Figure S1). These results suggested that both astrocytes and microglia were responsible for the inflammation in the acute phase of TBI.
As cellular excitotoxicity is a key mediator in the pathophysiology of TBI (Ng and Lee, 2019), we found that the upregulated genes in excitatory neurons of TBI were involved in hormone secretion, transport, and exocytosis. Considering that the release of glutamate was upregulated after TBI (Guerriero et al., 2015), we speculated that excitatory neurons might excessively transport and excrete glutamate in response to TBI. In contrast to a previous study that found CA1 neurons had higher expression levels of glutamate transporters and had the potential to differentiate or self-renew (Arneson et al., 2018), we found a neuron subpopulation as excitatory neurons, which presented an increase in the expression levels of genes involved in hormone transport and secretion and exocytosis. The sub-clustering analysis of ependymal cells revealed two subclusters C0 and C1. Notably, C0 was significantly enriched in TBI samples and characterized by enhanced activity of transition metal ion homeostasis and attenuated activity of cilium movement. As ependymal cilium could maintain cerebrospinal fluid flow (Xiong et al., 2014), we speculated that the attenuated activity of cilium movement after TBI might decrease cerebrospinal fluid flow.
To interpret the potential molecular basis of angiotensin receptor blocker, candesartan, for treating TBI, we conducted an integrative analysis of bulk and single-cell RNA-seq data to analyze cell type-specific gene expression changes. Specifically, we observed that downregulated genes were preferentially expressed by excitatory neurons in response to candesartan treatment, and were involved in pathways like neuronal system and neuroactive ligand-receptor interaction. These results indicated that candesartan might promote recovery after traumatic brain injury via mediating the neuroactive ligand-receptor interactions and reducing cellular excitotoxicity.
Compared with the previous single-cell studies (Arneson et al., 2018; Witcher et al., 2021), our study had three main distinctions. Firstly, we employed different statistical methods for cell proportion comparison between TBI and Sham groups. Specifically, we calculated the cell proportions for each sample (three Sham and three TBI replicates) and compared the cell proportions between TBI and Sham groups using t test, while the previous study (Arneson et al., 2018) merged the replicates into TBI or Sham groups and compared their cell proportions without considering the variance between samples when calculating the merged cell proportions. Secondly, we also observed concordance and discordance in the transcriptome changes of astrocyte, microglia and excitatory neurons between cortex and hippocampus after TBI.
Specifically, astrocyte activation was more significant in hippocampus than cortex, and it was in the astrocyte of hippocampus that inflammatory pathways were activated by TBI rather than in that of cortex. The seemingly contradictory results that the proportion of astrocytes was increased in hippocampal cells but decreased in the cortex, as well as the differences of most abundant cell types between cortex and hippocampus, might be due to the differences in cell-type compositions between cortex and hippocampus. Particularly, the major cell types that were primarily increased in TBI cortex and hippocampus are microglia and astrocyte, respectively. Moreover, as we measured the relative proportions of different cells, it can be inferred that the dramatic increase of microglia proportion might result in a decreased proportion of astrocyte in TBI cortex.
In addition, inflammatory pathways were activated in the microglia of both hippocampal and cortical TBI samples; however, interferon pathway was only activated in the microglia of cortical TBI samples. Glutamate transport and secretion were activated in the excitatory neurons of hippocampal TBI samples, but they remained unchanged in the excitatory neurons of cortical TBI samples. Thirdly, we also explored the molecular basis of angiotensin receptor blocker candesartan in the treatment of TBI, and found that candesartan might promote recovery after traumatic brain injury via mediating the neuroactive ligand-receptor interactions and reducing cellular excitotoxicity.
In conclusion, our study identified key cell types involved in and/or responding to TBI, which improved our understanding of the cellular and transcriptional changes after TBI, and of the molecular mechanisms that could serve as therapeutic targets.
referenc elink :https://www.frontiersin.org/articles/10.3389/fgene.2022.861428/full
Original Research: Open access.
“Uncovering temporospatial sensitive TBI targeting strategies via in vivo phage display” by Briana I. Martinez et al. Science Advances
