Alzheimer’s Disease Awareness Month

Alzheimer’s Disease (AD) is the most common cause of dementia, affecting an estimated 5,800,000 Americans (1,2). Many drug candidates to treat AD have emerged, but effective therapies are currently unavailable (3). Scientists continue to search for pathophysiological changes that contribute to AD and could become the target of new therapies.

Microglia are innate immune cells responsible for surveilling the brain and clearing debris and toxic proteins, including amyloid b and phosphorylated tau, which play a crucial role in AD onset and progression (5–7). Modulation of microglia function can potentially become a therapeutic target in AD (4–6). Data from genome-wide association studies indicate that changes in microglial gene expression increase susceptibility to AD (5–6,8). In particular, increased expression of the immunoregulatory receptor CD33, also known as sialic acid-binding immunoglobulin-type lectin 3 (Siglec-3), correlates with an increased risk of AD (9–12). Activation of CD33 suppresses microglial phagocytosis, migration, and proliferation, and its overexpression inhibits amyloid β clearance in vitro (12–14). As the name implies, Siglecs bind to endogenous glycoproteins or glycolipids carrying a sialic acid molecule (15). Thus, understanding and characterizing CD33 ligands present in the brain milieu can help pave the way to new therapeutics for AD.

Gonzalez-Gil et al. performed a series of biochemical experiments to isolate and characterize the structure of CD33 ligands in brain samples from patients with AD (16). Results revealed that AD brains express high levels of single sialoglycoprotein that binds to CD33 and Siglec-8, the most abundant Siglec on human microglia (16). 

Keep reading to learn the details of the Gonzalez-Gil et al. study, and check out other publication highlights on the blog. 

CD33 Binds to a Single Brain Sialoglycoprotein

In the first experiment, Gonzalez-Gil et al. sought to isolate and characterize CD33 ligands present in human brain samples. They collected post-mortem brain samples from 5 patients who died from AD and 5 age-matched controls. After homogenizing the samples, Gonzalez-Gil et al. performed western blots using CD33-Fc and Siglec-8-Fc chimeras. Results showed that both probes recognized a single glycoprotein with approximately 1 MDa.

Previous data from Gonzalez-Gil et al. have revealed that Siglec-8 selectively binds to sialic acid linked to a galactose carrying a sulfate ester (15). And CD33 displays a high affinity for this same type of structure (15). Researchers then investigated whether the glycoprotein recognized by CD33-Fc and Siglec-8-Fc carries the required sialic acid structure. Pre-treatment of brain homogenates with keratanase I (cleaves monosulfated disaccharides in keratan sulfate) or sialidase (hydrolyses sialic acid) eliminated the binding of CD33-Fc and Siglec-8-Fc to the glycoprotein of interest. However, pre-treatment with PNGase F (cleaves N-linked but not O-linked glycans) shifted the glycoprotein migration but spared its binding to CD33-Fc and Siglec-8-Fc. These results confirmed that endogenous CD33 and Siglec-8 ligands are sialoglycoproteins.

CD33 Ligand Comprises a Receptor Protein Tyrosine Phosphatase Zeta

Next, Gonzalez-Gil et al. performed mass spectroscopy, and the results revealed that a receptor protein tyrosine phosphatase zeta (RPTPζ) composes the protein portion of the newly isolated sialoglycoprotein. RPTPζ is a proteoglycan found both as a transmembrane protein tyrosine phosphatase and as a released extracellular form known as phosphacan.

Electrophoretic resolution revealed 3 large and 2 small isoforms of RPTPζ, but only the largest one co-migrated with CD33-Fc and Siglec-8-Fc. The largest isoform also co-eluted with CD33-Fc and Siglec-8-Fc in size-exclusion chromatography. Additional experiments confirmed that the same isoform of RPTPζ carries CD33 and Siglec-8 ligands. Gonzalez-Gil et al. performed western blots using anti-RPTPζ, CD33-Fc, Siglec-8-Fc probes, and fluorescent secondary antibodies. After overlaying the images, they observed that the band intensity increased, suggesting that all the different probes bound to the same molecule. After confirming the identity of the CD33 ligand, the authors named it RPTPζ^S3L.

To test the hypothesis that activation of CD33 by endogenous ligands might play a role in the pathogenesis of AD, Gonzalez-Gil et al. quantified the expression of RPTPζ^S3L in brain samples from patients with AD and age-matched controls. Results revealed that the concentration of RPTPζ^S3L was 2X higher in AD than in control brains.

Siglecs on Murine Microglia Bind to the Same Sialoglycan

Researchers also screened mouse brain samples for Siglecs that bind to human RPTPζ^S3L. Results revealed that Siglec-F, the mouse correspondent of human Siglec-8, co-migrated with RPTPζ^S3L (17). However, in Ptprz1-null mice—they don’t express RPTPζ—Siglec-F-Fc and anti-RPTPζ staining and co-migration were absent. Gonzalez-Gil et al. also developed transgene mice lacking enzymes essential to synthesizing sialoglycoproteins. Western blot results revealed that brain extracts from those knockout mice don’t bind to Siglec-F-Fc and Siglec-8-Fc. Together, these data suggest that Siglecs on human and mouse microglia bind to a similar sialoglycoprotein.

CD33 Ligand is Present in the Brain Milieu

In the last set of experiments, Gonzalez-Gil et al. performed immunohistochemistry to investigate the histological distribution of RPTPζ^S3L in non-AD human brain samples. After quenching endogenous HRP and AP activity with BLOXALL® Endogenous Blocking Solution, Peroxidase and Alkaline Phosphatase (SP-6000-100), researchers incubated brain samples with anti-human RPTPζ, CD33-Fc, or Siglec-8-Fc. After incubation with secondary antibodies, they quenched endogenous fluorescence in the tissue using Vector® TrueVIEW® Autofluorescence Quenching Kit (SP-8400-15). Results revealed that RPTPζ^S3L is present in the extracellular environment of human brain parenchyma. 

Future Perspectives

As future research confirms the role of CD33 and RPTPζ^S3L in AD pathophysiology, a new target for therapeutic intervention might emerge. Blocking the interaction of CD33 and RPTPζ^S3L could potentially prevent microglia inhibition and optimize amyloid b and phosphorylated tau clearance. The fact that Gonzalez-Gil et al. demonstrated that human and mouse Siglecs bind to the same sialoglycoproteins increases the translational impact of the acquired data. Drug development benefits from molecular structures that are well-conserved across different species.

Check out other resources in the blog, and stay tuned for more insights and research. 

References

1. Breijyeh Z, et al. 2020. Comprehensive Review on Alzheimer’s Disease: Causes and Treatment. Molecules.
2. Matthews KA, et al. 2018. Racial and Ethnic Estimates of Alzheimer’s Disease and Related Dementias in the United States (2015-2060) in Adults Aged ≥ 65 Years. Alzheimer’s & Dementia.
3. Cummings J, et al. 2022. Alzheimer’s Disease Drug Development Pipeline: 2022. Translational Research & Clinical Interventions.
4. Eskandari-Sedighi G, et al. 2023. CD33 Isoforms in Microglia and Alzheimer’s Disease: Friend and Foe. Molecular Aspects of Medicine.
5. Lewcock JW, et al. 2020. Emerging Microglia Biology Defines Novel Therapeutic Approaches for Alzheimer’s Disease. Neuron.
6. Salter MW, et al. 2017. Microglia Emerge as Central Players in Brain Disease. Nature Medicine.
7. Scheltens P, et al. 2021. Alzheimer’s Disease. The Lancet.
8. Schwabe T, et al. 2020. Shifting Paradigms: The Central Role of Microglia in Alzheimer’s Disease. Neurobiology of Disease.
9. Bertram L, et al. 2008. Genome-Wide Association Analysis Reveals Putative Alzheimer’s Disease Susceptibility Loci in Addition to APOE. American Journal of Human Genetics.
10. Hollingworth P, et al. 2011. Common Variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are Associated with Alzheimer’s Disease. Nature Genetics.
11. Naj AC, et al. 2011. Common Variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are Associated With Late-Onset Alzheimer’s Disease. Nature Genetics.
12. Griciuc A, et al. 2021. The Role of Innate Immune Genes in Alzheimer’s Disease. Current Opinion in Neurology.
13. Butler CA, et al. 2021. CD33M Inhibits Microglial Phagocytosis, Migration and Proliferation, but the Alzheimer’s Disease-Protective Variant CD33m Stimulates Phagocytosis and Proliferation, and Inhibits Adhesion. Journal of Neurochemistry.
14. Griciuc A, et al. 2013. Alzheimer’s Disease Risk Gene CD33 Inhibits Microglial Uptake of Amyloid Beta. Neuron.
15. Gonzalez-Gil A, et al. 2021. Siglec Ligands. Cells.
16. Gonzalez-Gil A, et al. 2022. Human Brain Sialoglycan Ligand for CD33, a Microglial Inhibitory Siglec Implicated in Alzheimer’s Disease. Journal of Biological Chemistry.
17. Morshed N, et al. 2020. Phosphoproteomics Identifies Microglial Siglec-F Inflammatory Response During Neurodegeneration. Molecular Systems Biology. 

Huntington’s Disease Awareness Month

Huntington’s disease (HD) develops due to a rare genetic mutation in the huntingtin gene (Htt), leading to progressive neurodegeneration in the cortex and striatum (1). Normal Htt contain about 18 CAG repeats, whereas mutated ones have 40 or more (2). The length of CAG repeat predicts the age of HD onset, but the length of polyQ repeats—encoded by CAG and CAA—is not as important to the overall HD pathogenesis (3–5). Once expressed, mutated huntingtin aggregates and triggers other neuropathological changes, including striatal-selective degeneration of medium spiny neurons (MSN), astrocytosis, and microgliosis (6). As a result, patients with HD develop motor dysfunction, cognitive impairment, and psychiatric symptoms (1). It’s estimated that HD affects about 5 in every 100,000 people worldwide, and a cure for this disease is currently unavailable (7). 

Preclinical models play a critical role in the study of HD pathophysiology and the development of new therapies. They help elucidate the molecular mechanisms leading to disease onset and progression and make testing the efficacy of new drugs easier. However, available preclinical models fail to replicate all aspects of human HD at once (8,9). New mice models combining more core characteristics of human HD can advance the knowledge of HD pathophysiology and potentially contribute to developing new therapies.  

With this goal in mind, Gu et al. developed and described a new transgenic mouse model of HD that expresses full-length human mutant huntingtin protein (9). They generated the new model using bacterial artificial chromosome (BAC), encoding about 120 uninterrupted CAG repeats, hence the name BAC-CAG. Mice developed many pathophysiological changes replicating human HD, including progressive motor deficits, sleep disturbance, striatal-selective nuclear inclusion, synaptic loss, astrogliosis, and microgliosis. Other key attributes of the new preclinical model of HD included minimal weight gain, somatic CAG repeat instability, and striatum-selective transcriptional dysregulation. In addition, data from the Gu et al. study revealed that striatal-selective neuropathogenesis associates with the length of CAG repeat.  

Keep reading to learn more about the Gu et al. study, and check out other publication highlights on the blog. 

The Need for Novel Preclinical Models of Human HD  

Many preclinical models of HD are available. Each particular model develops some characteristics of human HD, but no single model presents with them all (Table 1) (8). For example, knockin models of HD express mutant huntingtin—either human or murine, full-length or truncated—under the endogenous Htt gene locus (8). They develop motor deficits but don’t show signs of sleep disturbances, which are also commonly observed in HD patients (8). Other mouse models of HD were generated expressing full-length human mutant huntingtin using either BAC or yeast artificial chromosome (YAC) (8). BACHD and YAC128 are examples of HD mouse models commonly used in research studies, but many others exist (8). Overexpression of mutant protein in these models associates with unintended excessive weight gain, which is not a characteristic of human HD (Table 1). In addition, they fail to replicate many aspects of human HD pathogenesis, such as uninterrupted long CAG repeats and striatal-selective transcriptional dysregulation (Table 1) (8). This leads to a partial understanding of HD pathophysiology and limited applicability to the development of new drugs. 

The new preclinical model developed by Gu et al.—BAC-CAG—is a BAC transgenic mouse model that expresses full-length human mutant huntingtin with about 120 uninterrupted CAG repeats. BAC-CAG expresses huntingtin protein at a lower level than other mouse models of HD. Thus, BAC-CAG mice didn’t gain excessive body weight throughout the course of the study.  

BAC-CAG Mice Replicates Behavioral Alterations Observed in Human HD 

Gu et al. assessed behavioral alterations in BAC-CAG mice at different ages and observed that performance in the accelerated rotarod started to decline at 6 months. In this behavioral test, mice need to balance and walk forward on an accelerated rotating rod to avoid falling off, and latency to fall is recorded as a measure of motor coordination (10). Impairment in grip strength, another measure of motor function, developed later, at 12 months, in BAC-CAG mice.  

Patients with HD also develop sleep disturbances, and symptoms start to appear during the early stages of the disease (11). Likewise, BAC-CAG mice slept less and had a more fragmented sleep than wild-type mice. In addition, BAC-CAG mice showed reduced nighttime activity over 10 days—mice are nocturnal animals—compared with wild-type controls.   

Neuropathological Changes in HD Mice are Similar to Those Observed in Patients with HD 

Next, Gu et al. assessed whether BAC-CAG mice replicate various aspects of striatal-specific HD pathophysiology, including MSN loss, astrogliosis, microgliosis, presence of nuclear inclusions, and aggregation of mutant huntingtin (6). Using brain sections immunostained for Actn2, an MSN postsynaptic marker, Gu et al. observed that fluorescence intensity in the striata was lower in BAC-CAG than in wild-type mice at 12 months. Researchers also quantified MSN spine density using MORF3/Camk2a-CreER mice, which provides spatially spare fluorescent labeling of neuronal cells (12). In agreement with Actn2 immunofluorescence data, 12-month-old BAC-CAG mice displayed reduced spine densities in striata compared with wild-type mice.  

BAC-CAG mice showed morphological evidence of astrocytosis and microgliosis, other key hallmarks of human HD pathophysiology. Gu et al. performed immunostaining for GFAP, an astrocyte marker, in brain sections from 12-month-old BAC-CAG and wild-type mice. Quantification of immunofluorescence intensity revealed that BAC-CAG showed higher expression of GFAP in the striata and corpus callosum than wild-type mice. In addition, glial cells in BAC-CAG mice had a hypertrophic morphology. Together, both changes indicate that astrogliosis is part of the neuropathology of HD in the BAC-CAG mouse model. Researchers also quantified the number of Iba1+ and Gal3+ microglia cells in striata from 12-month-old BAC-CAG and wild-type mice. After immunohistochemistry and staining with Vector® SG Substrate Kit, Peroxidase (HRP), cell quantification revealed that BAC-CAG mice had more reactive microglia than wild-type mice.  

At 12 months, BAC-CAG mice exhibited striatum-selective nuclear inclusions containing mutant huntingtin, a feature of human HD present in knockin models but absent from other BAC and YAC transgenic mice. In addition, the striatum-selective nuclear inclusions further increased at 18 months, affecting about 98% of striatal neurons. BAC-CAG mice also showed the presence of aggregated mutant huntingtin in the striatum, which increased from 12 to 18 months. At 18 months, BAC-CAG mice also started to display aggregated mutant huntingtin in the cortex and cerebellum. However, researchers didn’t observe changes in soluble mutant huntingtin at any age.  

Transcriptional Dysregulation in BAC-CAG Mice Correlate with CAG Repeat Length 

BAC-CAG mice also displayed age-dependent striatum-selective transcriptional dysregulation. RNA-seq analysis at 2, 6, and 12 months showed that BAC-CAG mice exhibited dysregulation of gene expression in the striatum but not in the cortex. Mice exhibited transcriptional dysregulation as early as 6 months, but the number of differentially expressed genes increased with age. In addition, changes in gene transcription observed in BAC-CAG partially overlapped with those observed in the brains of patients with HD.  

Transcriptomic changes in the BAC-CAG model also shed light on a novel finding related to HD pathophysiology. Transcriptional dysregulation strongly correlated with the length of CAG repeats but not the length of polyQ. In knockin mice models of HD, the length of CAG and Q repeats matches. But because Q is encoded by CAG and CAA, human genomic models can have long Q repeats with short CAG repeats. Data from Gu et al. showed that CAG repeat length is a critical driving factor of HD transcriptionopathy. 

BAC-CAG mice also showed the presence of CAG repeat instability in somatic tissues, another pathological characteristic of human HD. Gu et al. observed the presence of PCR products amplified from human mutated huntingtin in the striatum, cortex, cerebellum, liver, heart, testis, and tail from 2-month-old BAC-CAG mice. In addition, at 12 months, somatic CAG instability increased in the striatum and liver but not in other tissue types from BAC-CAG mice.   

The presence of repeat-associated non-AUG (RAN) proteins translated from either CUG or CAG transcripts promotes cellular toxicity. Gu et al. used immunohistochemistry targeting the C-terminal region of polySer to detect the expression of RAN proteins on brain sections of 12, 18, and 22-month-old BAC-CAG mice. After incubation with primary and secondary antibodies, researchers used VECTASTAIN® Elite® ABC-HRP Kit, Peroxidase (Standard) and ImmPACT NovaRED® Substrate Kit, Peroxidase (HRP) to stain targeted cells. BAC-CAG but not wild-type mice expressed polySer RAN-positive cells in the striatum and cortex at 18 and 22 months. Researchers detected no changes in RAN protein levels in 12-month-old BAC-CAG mice. Most behavioral, pathological, and molecular changes start to develop in BAC-CAG mice at 12 months or earlier. Thus, the accumulation of RAN proteins is unlikely to contribute to disease onset but could contribute to disease progression.  

The new BAC-CAG mouse model of HD replicates more characteristics of human HD than any of the previous models. In addition, data acquired using BAC-CAG mice provided new insight into HD pathophysiology and revealed that CAG repeat length correlates with transcriptional dysregulation. The molecular, pathological, and behavioral characteristics of this new mouse model make it a promising candidate for testing therapies targeting gene expression levels and CAG repeat-induced toxicity. In addition, future studies using the BAC-CAG model might help to unravel new mechanisms underlying the pathophysiology of human HD. Altogether, these outcomes could potentially impact the lives of patients with this disease.   

Check out other resources in the blog to learn about other scientific advances and tips & tricks to improve your experiments.  

References 

1. Ross CA, et al. 2014. Huntington Disease: Natural History, Biomarkers and Prospects for Therapeutics. Nature Reviews Neurology.
2. Warby SC, et al. 2009. CAG Expansion in the Huntington Disease Gene is Associated With a Specific and Targetable Predisposing Haplogroup. The American Journal of Human Genetics.
3. Genetic Modifiers of Huntington’s Disease  (GeM-HD) Consortium. 2019. CAG Repeat Not Polyglutamine Length Determines Timing of Huntington’s Disease Onset. Cell.
4. Orr HT, et al. 2007. Trinucleotide Repeat Disorders. Annual Review of Neuroscience.
5. Wright GEB, et al. 2019. Length of Uninterrupted CAG, Independent of Polyglutamine Size, Results in Increased Somatic Instability, Hastening Onset of Huntington Disease. The American Journal of Human Genetics.
6. Vonsattel JPG, et al. 1998. Huntington Disease. Journal of Neuropathology & Experimental Neurology.
7. Medina A, et al. 2022. Prevalence and Incidence of Huntington’s Disease: An Updated Systematic Review and Meta-Analysis. Movement Disorders.
8. Ferrante RJ. 2009. Mouse Models of Huntington’s Disease and Methodological Considerations for Therapeutic Trials. Biochimica et Biophysica Acta (BBA) – Molecular Basis of Disease.
9. Gu X, et al. 2022. Uninterrupted CAG Repeat Drives Striatum-Selective Transcriptionopathy and Nuclear Pathogenesis in Human Huntingtin BAC Mice. Neuron.
10. Deacon RMJ. 2013. Measuring Motor Coordination in Mice. Journal of Visualized Experiments.
11. Morton AJ. 2013. Circadian and Sleep Disorder in Huntington’s Disease. Experimental Neurology.
12. Veldman MB, et al. 2020. Brainwide Genetic Sparse Cell Labeling to Illuminate the Morphology of Neurons and Glia with Cre-Dependent MORF Mice. Neuron.

Colorectal Cancer Awareness Month

The development of immunotherapy has revolutionized cancer care (1). These drugs block tumor-induced immunosuppression and help immune cells detect and attack cancer cells (1). Immunotherapy effectively prevents the progression of many types of cancer but has limited effect on colorectal cancer (CRC), suggesting that this type of cancer uses different strategies to evade immune recognition (2). CRC ranks third among the most common types of cancer and second among cancers leading to death worldwide (2). Identifying the mechanisms involved in CRC immune evasion can help the development of new therapies to improve clinical outcomes.   

Using a combination of in vitro and in vivo experiments, Silva et al. showed that expression of branched N-glycans in CRC cells contributes to immune suppression and evasion (3). In addition, changing the glycosylation profile of cancer cells restored anti-tumor activity (3).  

Keep reading to learn more about this study and check out other publication highlights on the blog. 

The Role of Glycans in Cancer Biology  

Cancer cells have a different glycosylation signature, or glycocalyx, than healthy cells (4,5). Glycan-binding receptors on the surface of immune cells recognize the glycocalyx of tumor cells and, in response, trigger immune activation (6,7). Examples of these glycan-binding receptors include galectins, Siglecs, and C-type lectins—dendritic cell-specific intracellular adhesion molecular-3-grabbing nonintegrin (DC-SIGN) and mannose receptors (6,7). However, tumor cells change their glycocalyx to drive cancer progression (4,5). For example, overexpression of b1,6-GlcNAc-branched N-glycans in gastrointestinal cancer cells often associates with an invasive tumor phenotype and poor clinical prognosis (8–12).  

Despite the known association between overexpression of branched N-glycans and tumor progression, additional research is needed to elucidate the precise mechanisms mediating this relationship. The long-term goal is to identify new therapeutic targets to treat CRC and other types of cancer.  

Overexpression of Branched N-Glycans in Clinical Samples 

In the first set of experiments, researchers used human CRC samples to confirm previous findings: Overexpression of branched N-glycans associates with tumor progression. First, Silva et al. used fluorescein-conjugated Phaseolus vulgaris leucoagglutinin and Galanthus nivalis to target the b1,6-GlcNAc arm of branched N-glycans and terminal a-1,3-mannose residues, respectively. Then, they used immunohistochemistry (IHC) to quantify the expression of FOX3P in Tregs (T-regulatory) cells and Tbet in CD4+ T lymphocytes. Data showed that as the stage of CRC advances, the expression of b1,6-GlcNAc-branched N-glycans increases and of mannosylated N-glycans decreases. In addition, changes in the cancer cell glycocalyx were associated with more FOX3P-expressing Tregs cells and fewer Tbet-expressing cells in the tumor environment.   

Transcriptomic analysis confirmed that FOXP3 expression gradually increases as cellular phenotype goes from normal dysplasia to colon adenocarcinoma. Researchers also quantified the levels of MGAT5, the gene that encodes GnT-V, the enzyme responsible for the expression of b1,6-GlcNAc-branched N-glycans. Data showed that the expression of MGAT5 steadily increases as the stage of human CRC progresses and positively correlates with FOXP3 levels. Silva et al. also reported a strong positive correlation between FOXP3 and MGAT5 expression in large datasets from patients with colorectal cancer.  

Overexpression of Branched N-Glycans Promotes Immunosuppression 

Next, researchers sought to establish the causal relationship between the overexpression of branched N-glycans and immunosuppression. They transfected a gastrointestinal cancer cell line with the GnT-V enzyme to overexpress b1,6-GlcNAc-branched N-glycans. Transfected and mock cells were co-cultured with CD4+ T lymphocytes and dendritic cells. Overexpression of branched N-glycans in transfected cancer cells suppressed the release of cytokines IFN-g, TNF-a, IL-6, and IL-8 by immune cells. In addition, expression of MHC-I in transfected cancer cells was higher in the intracellular compartment than on the cell surface, suggesting that the presence of branched N-glycans promotes the internalization of MHC-I.  

Mock and transfected cells displayed opposite glycoprofile—mock cells had high levels of mannose-enriched glycans, and transfected cells overexpressed branched N-glycans. These differences in the glycocalyx likely impact the interaction and communication of cancer with immune cells. To investigate this hypothesis, researchers performed an assay to assess the binding between C-type lectin receptors on immune cells and glycans on mock and transfected cells. Mock cells displayed a high affinity for DC-SIGN binding, which decreased with overexpression of branched N-glycans in transfected cells. Overall, data suggest that DC-SIGN receptors on immune cells have a high affinity for mannose enriched-glycans on healthy and early-stage cancer cells. But as the tumor stage progresses, the overexpression of branched N-glycans masks the recognition of CRC cells by DC-SIGN, resulting in impaired immune activation.  

Removal of Branched N-Glycans Rescues Anti-Tumor Activity 

Silva et al. also showed that modulation of N-glycosylation in tumor cells can impact tumor progression in preclinical models. Researchers used kifunensine (KF) to inhibit N-glycosylation in the MC38 murine colon adenocarcinoma cell line. As a result, the expression of high-mannose N-glycans increased and that of branched N-glycans decreased. Then, immunocompetent mice received subcutaneous inoculation of MC38 plus KF cells or MC38 plus vehicle cells. Inhibition of N-glycosylation in MC38 cells contributed to a significant delay in tumor growth.  

As an additional proof of concept, researchers used CRISPR-Cas9 to silence the MGAT5 gene (encodes GnT-V enzyme) in MC38 cells, resulting in the generation of 3 different clones. Next, they used P. vulgaris leucoagglutinin, G. nivalis, and biotinylated Concanavalin A to analyze the glycoprofile of each clone and validate the functional knockout of the enzyme. The clone with the lowest expression of branched N-glycans was inoculated into immunocompetent mice. Results confirmed that low expression of branched N-glycans contributes to suppression of tumor growth—only 1 of 11 mice developed a very small tumor. In addition, the removal of branched N-glycans impacted the immune response. Inhibition of N-glycosylation associated with a higher number of immune cells and increased expression of cytokines. Data also revealed that inhibition of N-glycosylation enhances immune recognition of cancer cells but doesn’t impact the tumor’s capacity to grow. Inoculation of wild-type and MGAT5-/- MC38 cells in immunocompromised mice resulted in tumor growth, regardless of the absence of branched N-glycans. Therefore, immune recognition of high-mannose glycans in tumor cells is essential to suppress tumor growth.  

In a final experiment, Silva et al. crossed over a preclinical model of intestinal tumorigenesis with MGAT5-/- mice. Deleting the MGAT5 gene resulted in fewer tumors with smaller sizes and more prolonged survival. The absence of branched N-glycan overexpression also resulted in increased infiltration of immune cells, decreased number of FOX3P Tregs and M2 pro-tumor macrophages, and enhanced release of pro-inflammatory cytokines. Similar findings in different preclinical models of CRC reinforced the overarching conclusion that removing branched N-glycans from the tumor glycocalyx reduces immune evasion.  

Clinical Relevance 

Characterizing the mechanism of immune evasion in CRC has a significant translational impact on public health. CRC is the third most common type of cancer, and many patients don’t respond to currently available therapies (2). Data from Silva et al.’s study provide robust evidence that the glycosylation profile of cancer cells plays a major role in the immune evasion process. Modulation of glycosylation improved anti-tumor activity in in vitro and in vivo experiments. Continued research on this topic can contribute to identifying therapeutic targets and developing new interventions to treat CRC. 

If you want to learn more about the applications of glycobiology in cancer research, check out the Examining Altered Glycobiology in Cancer eBook, and stay tuned to the blog for more glycobiology highlights.  

References 

1. Esfahani K, et al. 2020. A Review of Cancer Immunotherapy: From the Past, to the Present, to the Future. Current Oncology.
2. Weng J, et al. 2022. Exploring Immunotherapy in Colorectal Cancer. Journal of Hematology & Oncology.
3. Silva MC, et al. 2020. Glycans as Immune Checkpoints: Removal of Branched N-Glycans Enhances Immune Recognition Preventing Cancer Progression. Cancer Immunology Research.
4. Marth JD, et al. 2008. Mammalian Glycosylation in Immunity. Nature Reviews Immunology.
5. Pinho SS, et al. 2015. Glycosylation in Cancer: Mechanisms and Clinical Implications. Nature Reviews Cancer.
6. Pereira MS, et al. 2018. Glycans as Key Checkpoints of T Cell Activity and Function. Frontiers in Immunology.
7. van Kooyk Y, et al. 2008. Protein-Glycan Interactions in the Control of Innate and Adaptive Immune Responses. Nature Immunology.
8. Carvalho S, et al. 2015. Preventing E-Cadherin Aberrant N-Glycosylation at Asn-554 Improves Its Critical Function in Gastric Cancer. Oncogene.
9. Carvalho S, et al. 2016. O-Mannosylation and N-glycosylation: Two Coordinated Mechanisms Regulating the Tumour Suppressor Functions of E-Cadherin in Cancer. Oncotarget.
10. Carvalho S, et al. 2016. Cadherins Glycans in Cancer: Sweet Players in a Bitter Process. Trends in Cancer.
11. Pinho SS, et al. 2013. E-Cadherin and Adherens-Junctions Stability in Gastric Carcinoma: Functional Implications of Glycosyltransferases Involving N-Glycan Branching Biosynthesis, N-Acetylglucosaminyltransferases III and V. Biochimica et Biophysica Acta (BBA) – General Subjects.
12. Pinho SS, et al. 2009. The Role of N-Acetylglucosaminyltransferase III and V in the Post-Transcriptional Modifications of E-Cadherin. Human Molecular Genetics.
13. Taniguchi N, et al. 2015. Glycans and Cancer: Role of N-glycans in Cancer Biomarker, Progression and Metastasis, and Therapeutics. Advances in Cancer Resesarch.

Heart Health Awareness Month

Heart diseases comprise many different conditions, and together, they are responsible for about 20% of all deaths in the United States (1). Coronary heart diseases—blockage or narrowing of the heart’s main blood vessels—are the most common type of heart disease and can lead to myocardial infarction (MI), a serious and life-threatening condition (1). MI happens when blood flow to the heart completely stops. As a result, lack of oxygen and nutrients results causes damage to the heart muscle and contribute to heart failure (1).  

Current treatments for MI focus on preventing reoccurrence. Patients often receive medications to prevent blood clots, improve blood flow, slow heart rate, and reduce blood pressure (2). Clinical management of MI still lacks interventions focused on counteracting pathophysiological changes and preventing damage to the heart muscle. The development of such treatments can have a major impact on public health, as it has the potential to improve health outcomes in patients who have had MI.  

Researchers from the Oregon Health and Science University, Sepe et al., characterized pathophysiological changes in the heart in response to novel therapeutics that disrupt protein tyrosine phosphatase-s signaling (3). They observed that the treatment restores sympathetic innervation and shifts the immune response after MI to promote tissue repair. As a result, heart function improved and susceptibility to arrhythmia decreased (3). 

Keep reading to learn more details about the research study, and check out the blog for other publication highlights. 

Myocardial Infarction Pathophysiology  

After MI, 2 waves of immunological response recruit and activate innate and adaptative immune cells to clear cellular debris and remodel the infarcted heart (4). A pro-inflammatory response characterizes the initial phase: presence of M1 macrophages, release of pro-inflammatory cytokines, proteolysis, and phagocytosis (4). In the second phase, the pro-inflammatory response tapers off (but doesn’t fully resolve), and the healing and remodeling processes begin (4). The number of reparative immune cells, such as M2 macrophages and regulatory T cells (Tregs), increases, contributing to the development of a mature scar (4). Persistence of the inflammatory response beyond the initial phase often results in pathological remodeling of the myocardium and contributes to heart failure (4). 

MI pathophysiology also includes reperfusion-induced sympathetic nerve damage (5,6). And chondroitin sulfate proteoglycans in the cardiac scar activate protein tyrosine kinase phosphatase receptor-s on sympathetic nerves and prevent nerve regeneration even in the presence of nerve growth factor (5). In the end, the extent of nerve damage predicts the development of ventricular arrhythmias (7–9).  

Study Rationale and Hypothesis 

Previous studies have identified 3 novel therapeutics that can promote sympathetic reinnervation in the heart after MI: Intracellular sigma peptide (ISP), HJ-01, and HJ-02 (6,10,11). ISP prevents the binding of chondroitin sulfate proteoglycans to protein tyrosine phosphatase-s, and HJ-01 and HJ-02 disrupt protein tyrosine phosphatase-s–tropomyosin kinase A interactions (6,10,11). As a result, sympathetic nerves can regrow even in the presence of chondroitin sulfate proteoglycan. In addition, disrupting protein tyrosine phosphatase receptor-s normalizes heart function and confers resistance to isoproterenol-induced arrhythmias (6). 

Sepe et al. conducted experiments to validate previous findings and determine the impact of treatments with ISP, HJ-01, and HJ-02 on the profile of the immune cells after MI. They hypothesized that therapeutics would shift the immune response into a reparative phenotype and used quantitative multiplex immunohistochemistry (mIHC) to test their hypothesis. 

Modulation of Immune Response 

Mice underwent 2 surgeries: The first one to implant telemetry electrodes in the heart, and the second one, 5 days later, to induce ischemia-reperfusion. For the latter, researchers occluded the left coronary artery for 45 minutes and then released the ligature to induce reperfusion. Sham mice underwent surgery but had no occlusion. Between 3–10 days after surgery, mice received daily intraperitoneal injections of ISP, HJ-01, HJ-02, or vehicle. Data collection took place 14–15 days after surgery. 

As previous studies have shown, treatment with ISP, HJ-01, and HJ-02 promoted sympathetic reinnervation of the heart, as assessed by immunohistochemistry (IHC) for tyrosine hydroxylase (5,6). Mice that received treatment had sympathetic nerve density similar to that of sham animals. In addition, sympathetic reinnervation of the heart resulted in functional improvement. Mice that received treatment had fewer isoproterenol-induced arrhythmia than mice that received vehicle.  

Next, researchers used mIHC to phenotype immune cells in the heart after MI. They performed 15 rounds of IHC to target a total of 23 cell markers. Each round of the mIHC process consisted of antigen retrieval, incubation with primary and secondary antibodies, staining with ImmPACT® AEC Substrate Kit, Peroxidase (HRP), slide visualization and image acquisition, and stripping (Figure 1). The subsequent image analysis process took place in 3 steps: Image processing, cell classification, and quantification of cell types (Figure 1). 

Alzheimer’s disease (AD) is a progressive neurodegenerative condition that leads to brain atrophy, memory loss, and confusion. Scientists continue to search for the answer to many unresolved questions in the pathophysiology of AD. One of those areas revolves around the factors contributing to selective neurodegeneration—the observation that some cells die while others remain resilient (1). This selective vulnerability is characteristic of many neurodegenerative diseases and, in AD, has been observed in some neuronal populations in the hippocampus (2–4). The factors underlying selective neurodegeneration are mostly unknown, and discoveries in this area may directly impact the development of new therapies for AD.

Using single-nucleus RNA sequencing (snRNA-seq), Zalocusky and colleagues showed that expression of apolipoprotein (Apo) E in neurons could be one of the factors contributing to selective vulnerability in AD (4). Data from their study provide robust evidence that increased levels of ApoE in neurons drive the expression of immune function genes, contributing to morphological and functional changes characteristic of AD.

Keep reading to understand the details of this valuable scientific discovery as we highlight impactful research for Alzheimer’s Awareness Month. 

Common Factors in Vulnerable Neurons

In the search for common characteristics of the vulnerable neuronal population, Zalocusky et al. focused on the pathological role of ApoE. As with any other lipoprotein, ApoE plays a vital role in lipid metabolism. In the brain, ApoE is mainly produced in astrocytes. Its neuronal expression associates with stress, injury, and aging and contributes to impaired synaptic plasticity, tau pathology, learning, and memory deficit. Different isoforms—ApoE2, ApoE3, and ApoE4—have been characterized, of which ApoE3 is the most common (9). Humans carrying the allele for ApoE4 have an increased risk for AD and decreased age on onset (2,3,10). Expression of human ApoE4 in mouse models results in tau pathology, neuroinflammation, and neuronal loss (11).

To identify common factors that could potentially associate with selective vulnerability, Zalocusky et al. performed gene profiling in various neuronal populations. They dissected hippocampi from female mice expressing human ApoE3 (ApoE3-KI) and ApoE4 (ApoE4-KI) and isolated nuclei from various neuronal populations. Using snRNA-seq, Zalocusky et al. analyzed a total of 123,489 nuclei and 21,204 genes. Results revealed a total of 27 clusters of cells, with 16 being neuronal clusters. Regression analyses showed that ApoE expression explained 59–82% of within-cell variability depending on the cell cluster. Researchers also used to identify other functional pathways associated with ApoE expression. Results revealed that ApoE correlated with genes involved with metabolism, neurodegeneration, cellular senescence and apoptosis, DNA damage and repair, immune response, autoimmunity, and response to infections.

Using animal models to investigate the mechanisms underlying disease pathophysiology is a convenient approach that gives the investigator total control over the experimental design. However, when the long-term goal of a research study is to inform the development of new therapies, examining whether the data replicate in humans is essential. Zalocusky et al. profiled gene expression in neuronal cells from the brains of patients with mild cognitive impairment or Alzheimer’s dementia. Results showed that, on average, 28% of neurons expressed ApoEvaried with age and disease stage. Similar to animal model findings, pathway analysis in human cells revealed that ApoE expression correlated with genes associated with cellular metabolism, neurodegeneration, DNA damage and repair, immune response, autoimmunity, and response to infections. Together, gene profiling data suggest that neuronal ApoE expression is potentially an important driver of within-cell-type variability in both mouse and human brains.

Temporal Relationship Between ApoE Expression and Disease Progression 

Next, Zalocusky et al. assessed ApoE expression in neurons from ApoE3-KI and ApoE4-KI mice at different ages. They observed that the proportion of neurons expressing high levels of ApoE peaks at a specific time and then goes down. In ApoE3-KI mice, the peak happened at 20–21 months, and in ApoE4-KI mice, at 15–16 months. The authors suggest that the decline in the proportion of neurons expressing high levels of ApoE after its peak could indicate that ApoE expression drives neuronal loss.

Researchers also showed that this temporal change in ApoE expression follows a similar pattern in neurons from human brain cells. They observed a low proportion of neurons expressing high levels of ApoE in individuals with no cognitive impairment. Patients with mild cognitive impairment had the highest proportion of neurons expressing high levels of ApoE. Mild cognitive impairment often develops in the early stages of AD and is characterized by memory or thinking problems such as forgetting events or appointments, trouble navigating familiar locations, and a hard time finding the right word to express an idea or thought (12). As AD progresses, cognitive impairment becomes more severe and patients develop dementia. In patients with AD, Zalocusky et al. observed a relatively low proportion of neurons expressing high levels of ApoE. Data from human brain cells support the same conclusions drawn from animal data. Neuronal ApoE expression increases during the early stages of AD and declines as the disease progresses. Could ApoE be one of the driving factors of neuronal loss in AD?

Testing the Causal Relationship Between ApoE Expression and Neuronal Loss

Following the above study, Zalocusky et al. turned off the expression of human ApoE in neurons and investigated its impact on neuronal and synaptic loss. All the other cell types in the conditional knockout mouse model continued to express human ApoE. Age-matched mice expressing human ApoE served as controls for this experiment. Then, they used immunohistochemistry for NeuN (a neuron-specific marker) and PSD95 (a protein essential for the formation of synapses) to quantify changes in neuronal and synaptic density, respectively As some of the antibodies used in the immunohistochemistry were raised in mice, researchers used M.O.M.^® (Mouse-on-Mouse) Blocking Reagent to optimize the staining and reduce unspecific background. After incubating the slices with appropriate secondary antibodies and mounting the slides with VECTASHIELD^® Antifade Mounting Media with DAPI, Zalocusky et al. quantified NeuN⁺ cells and PSD95 immunofluorescence intensity. Data showed that neuron-specific knockout of the ApoE gene results in higher neuron density, larger hippocampal volume, and preservation of synaptic proteins.

Initial pathway analysis revealed that ApoE expression in neurons strongly correlated with immune function-related genes. Within those, MHC genes showed a prominent correlation with ApoE expression on a cell-by-cell basis. Lack of ApoE expression resulted in the downregulation of MHC gene expression at both RNA and protein levels. Functional expression of MHC-I genes requires the protein B2M (15,16). As a next step, Zalocusky et al. silenced B2M expression in primary neurons expressing human ApoE4, which are cells that accumulate phosphorylated tau in the neuronal soma (15,17). Knockdown of B2M resulted in reduced expression of B2M and MHC-I, but most interestingly, also reduced phosphorylated tau in the soma primary neurons expressing human ApoE4. As expected, ApoE4 expression remained unaltered.

Zalocusky et al. also induced the expression of human pathological tau in wild-type and B2M-knockout mice. Researchers used immunostaining followed by impregnation to detect tau pathology in brain slices. The use of Avidin/Biotin Blocking Kit and a ensured low background and optimal staining, and results showed that B2M-knockout mice had reduced tau pathology. Lastly, Zalocusky et al. observed correlations between MHC-I genes and tau tangle pathology in humans. Regression analysis revealed that MHC-I expression predicts tau pathology in human brains even when controlling for age, sex, ApoE genotype, ApoE level, and AD clinical status.

Future Implications 

The Zalocusky et al. study provides robust evidence that ApoE expression in neurons drives activation of the immune response and selective vulnerability in AD. The cascade of events that unfolds after neuronal expression of ApoE includes expression of MHC-I, tau pathology, synaptic dysfunction, and neuronal loss. Overall conclusions come from data gathered from human samples and animal models, strengthening the findings’ translatability. As with any discovery, many questions remain unanswered. For example, what triggers ApoE expression in neurons? Are there other components mediating the relationship between ApoE and neuronal loss? Despite unanswered questions, these data provide new mechanistic insight into the pathophysiology of AD, which opens the possibility for new treatments. New therapies could individually target different components of the newly discovered cascade. However, the authors suggest that the best results would likely come from an intervention that combines multiple drugs targeting different components of the ApoE-MHC-neuronal loss axis.

If you want to learn about other innovative findings, check out other publication highlights, and be sure to stay tuned into the blog for more insights.

References

1. Fu H, et al. 2018. Selective Vulnerability in Neurodegenerative Diseases. Nature Neuroscience.
2. Huang Y, et al. 2012. Alzheimer Mechanisms and Therapeutic Strategies. Cell.
3. Najm R, et al. 2019. Apolipoprotein E4, Inhibitory Network Dysfunction, and Alzheimer’s Disease. Molecular Neurodegeneration.
4. Zalocusky KA, et al. 2021. Neuronal ApoE Upregulates MHC-I Expression to Drive Selective Neurodegeneration in Alzheimer’s Disease. Nature Neuroscience.
5. Wang C, et al. 2018. Gain of Toxic Apolipoprotein E4 Effects in Human iPSC-Derived Neurons is Ameliorated by a Small-Molecule Structure Corrector. Nature Medicine.
6. Xu PT, et al. 1999. Specific Regional Transcription of Apolipoprotein E in Human Brain Neurons. The American Journal of Pathology.
7. Xu Q, et al. 2006. Profile and Regulation of Apolipoprotein E (ApoE) Expression in the CNS in Mice With Targeting of Green Fluorescent Protein Gene to the ApoE Locus. The Journal of Neuroscience.
8. Andrews-Zwilling Y, et al. 2010. Apolipoprotein E4 Causes Age- and Tau-Dependent Impairment of GABAergic Interneurons, Leading to Learning and Memory Deficits in Mice. The Journal of Neuroscience.
9. Fernández-Calle R, et al. 2022. APOE in the Bullseye of Neurodegenerative Diseases: Impact of the APOE Genotype in Alzheimer’s Disease Pathology and Brain Diseases. Molecular Neurodegeneration.
10. Farrer LA, et al. 1997. Effects of Age, Sex, and Ethnicity on the Association Between Apolipoprotein E Genotype and Alzheimer Disease. A Meta-Analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA.
11. Shi Y, et al. 2017. ApoE4 Markedly Exacerbates Tau-Mediated Neurodegeneration in a Mouse Model of Tauopathy. Nature.
12. Chua TC, et al. 2008. Diffusion Tensor Imaging in Mild Cognitive Impairment and Alzheimer’s Disease: A Review. Current Opinion in Neurology.
13. Broadhead MJ, et al. 2016. PSD95 Nanoclusters are Postsynaptic Building Blocks in Hippocampus Circuits. Scientific Reports.
14. Gusel’nikova VV, et al. 2015. NeuN as a Neuronal Nuclear Antigen and Neuron Differentiation Marker. Acta Naturae.
15. Ballatore C, et al. 2007. Tau-Mediated Neurodegeneration in Alzheimer’s Disease and Related Disorders. Nature Reviews Neuroscience.
16. Germain RN, et al. 1993. The Biochemistry and Cell Biology of Antigen Processing and Presentation. Annual Review of Immunology.
17. Braak H, et al. 1991. Neuropathological Stageing of Alzheimer-Related Changes. Acta Neuropathologica.

Every bit of progress in the research and development of new treatments for spinal muscular atrophy (SMA) counts as a big win. Spinal muscular atrophy is a serious genetic condition that results in the degeneration of motor neurons. As a result, patients with SMA develop muscle weakness, atrophy, and paralysis, eventually leading to death (1). A cure for SMA is currently unavailable, but different treatment approaches can come together to advance the management of SMA symptoms and improve patients’ quality of life. 

SMA is a rare disease caused by a deletion or mutation to the survival motor neuron 1 (SMN1) gene. It affects 1 to 2 individuals per 100,000 newborns (1). Without adequate levels of SMN protein, motor neurons cannot survive, and thus, muscles can’t function (1). Although patients with SMA still have the SMN2 gene, they don’t express enough SMN protein to support motor neuron viability and muscle function (1).  

SMA phenotypes are classified into 4 types according to the age of onset, the level of motor dysfunction, and the age at death (1): 

• SMA type 1 is the most common type and accounts for 60% of all cases of the disease. Symptoms appear at birth or within the first six months. Infants don’t meet typical milestones, and death often occurs before their second birthday. 
• In type 2, symptoms emerge between 6–18 months and mostly affect lower limbs. Children can sit but can’t walk and might live into adulthood.  

• Patients with type 3 may start to develop symptoms after 18 months, but some won’t show symptoms until adulthood. Symptoms include mild muscle weakness, difficulty walking or standing, and frequent respiratory infections. Type 3 doesn’t shorten life expectancy. 
• Type 4 is a rare form in which the onset of symptoms usually happens in the mid-30s. Patients present with slow progression of muscle weakness, and most people remain mobile and live full lives. 

Although a cure for SMA is currently unavailable, the Food and Drug Administration (FDA) has approved some interventions, including gene therapy with onasemnogene abeparvovec (2). This therapy uses a virus that crosses the blood-brain barrier to deliver a functional copy of the SMN gene to target motor neurons. Clinical trial data show that intervention improves symptoms, and infants who receive onasemnogene abeparvovec live longer and have a reduced need for respiratory support than non-treated patients (3,4). Some infants could sit unassisted, and a few could even walk (3,4).  

Keep reading to learn more about research done with specimens from patients who received abeparvovec and another SMA-related preclinical study. If you want to read about scientific advances in additional fields of research, check out other publication highlights here on the blog. 

Gene therapy for SMA can change patients’ phenotypes 

Despite available evidence confirming clinical efficacy, few studies have investigated the distribution of the vector genome across different tissue types and its impact on the expression of the SMN protein after treatment with onasemnogene abeparvovec. Intending to fill this gap, Thomsen et al. used post-mortem tissue to investigate the biodistribution of the SMN gene and protein across the central nervous system (CNS) and peripheral organs (5). Researchers used post-mortem specimens from patients who had SMA type 1 (SMA1), received onasemnogene abeparvovec (single intravenous administration), and died of treatment-unrelated respiratory complications. One of the two patients experienced an improvement in motor function while the other died shortly after administration and didn’t show any clinical improvement. The research team then used various molecular and cellular techniques to investigate the biodistribution of the vector genome, mRNA transcript, and SMN protein in multiple tissues. Results showed that the vector genome was present in motor neurons from both patients. Other CNS (brain and spinal cord) and peripheral (muscle, liver, and thymus, among others) tissues also contained the vector genome. Next, Thomsen et al. observed that onasemnogene abeparvovec mRNA transcript was present in tissue samples from only one patient, as mRNA degradation likely prevented detection in specimens from the other patient.  

Classic immunohistochemistry techniques then allowed the researchers to assess the distribution of SMN protein in various tissues. They analyzed specimens from patients with SMA who didn’t receive treatment and one patient without SMA1. Preparation of samples from different patients included formalin-fixed paraffin embedding or flash-freezing followed by post-fixation. Following subsequent steps applicable to each preservation technique, samples were blocked to reduce non-specific binding and incubated with a specific primary antibody. Researchers then used biotinylated goat anti-mouse secondary antibody, a VECTASTAIN^® HRP- ABC Kit, and a Vector^® NovaRED™ Substrate Kit to detect the target SMN protein. Results revealed that patients with SMA1 who received treatment expressed more SMN protein in spinal cord motor neurons than non-treated patients with SMA1. Immunostaining also revealed that patients who received onasemnogene abeparvovec also expressed the SMN protein in neuronal and glial cells in other CNS regions.   

Thomsen et al. also assessed the expression of the choline acetyltransferase (ChAT) enzyme, a motor neuron-specific marker, in tissue from treated and non-treated patients with SMA. Following steps similar to the ones performed for immunodetection of SMN protein and swapping the choice of biotinylated secondary antibody for horse anti-goat, they observed that ChAT was absent or expressed at low levels in control SMA tissue. However, in tissue from patients with SMA who received treatment, the number of ChAT-positive motor neurons doubled relative to untreated patients. Despite this significant increase, the number of ChAT-positive motor neurons in treated tissue was still half that observed in non-SMA control tissue.   

Data from Thomsen et al. represent significant progress in SMA research. Even though results don’t translate as a cure or long-term clinical management for this disease, they show that it’s possible to use a vector genome to increase the expression of the SMN protein, resulting in detectable yet limited improvement of motor function. The development of pharmacological interventions targeting other aspects of the SMA pathophysiology can further improve the management of SMA symptoms. Simon et al. have shown that pharmacological increase of neuronal activity can help improve motor neuron function in a preclinical model of SMA (6). 

Increase of neuronal activity improves synaptic transmission in SMA 

During development, neuronal activity is essential for the formation, refinement, and maintenance of the connection between motor neurons and muscle fibers. Various molecular signals attract the motor neuron to the muscle fiber, and neuronal activity strengthens and maintains the neuromuscular junction (NMJ). However, the contribution of neuronal activity (or lack of it) to the progression of SMA is an unexplored topic. Simon et al. explored the impact of pharmacological manipulation of neuronal activity on synaptic function at the NMJ in an animal model of SMA (6). They used 4-amino-pyridine (4-AP), a drug that promotes the efflux of potassium, to increase neuronal activity and hypothesized this intervention could ameliorate some of the muscular dysfunction (6).   

Mice don’t have the SMN2 gene, thus, generating a preclinical model for SMA required deleting the SMN1 and adding the SMN2 gene that expresses full-length SMN at low levels (7). Motor neurons in the resulting SMAD7 mouse model exhibit low activity levels, which leads to muscle dysfunction and eventually neuronal death (8–10). In Simon et al.’s study, a single intraperitoneal injection of 4-AP in SMA mice increased the expression of c-Fos, a marker for neuronal activity, in motor neurons, other spinal cord neurons, and dorsal root ganglia sensory neurons (11). Next, chronic intraperitoneal administration of 4-AP (twice a day; from birth to death) improved motor reflexes, ability to walk, and survival in SMA mice. Wild-type mice, however, didn’t show changes in motor reflexes, body weight, and survival after receiving chronic 4-AP. It’s important to note that the improvement observed in SMA mice was independent of SMN protein expression, as its levels didn’t change in response to treatment. Chronic 4-AP administration didn’t prevent or delay neuronal loss either.  

The next logical question became: What are the changes underlying the functional improvement observed after chronic 4-AP administration? To answer this question, researchers used confocal microscopy to assess changes in the number of synapses between motor neurons and muscle fibers. They used VECTASHIELD^® PLUS Antifade Mounting Medium to help prevent photobleaching while acquiring z-stacks. Quantitative analyses of photomicrographs revealed that boosting neuronal activity with 4-AP promotes axonal sprouting, or in other words, increases the number of synapses at the NMJ. However, significant increases only happened at later stages of development (P11), not earlier stages (P6). These data indicate that neuronal activity-induced axonal sprouting can compensate for the loss of motor neurons in SMA, resulting in motor function improvement.   

Simon et al. had previously shown that inhibition of the p53 pathway with PFT (Pifithrin-a) prevents death of motor neurons but has no effect on the number and function of synapses (12). Could co-treatment with 4-AP and PFT have an additive effect? In a final experiment, researchers performed daily co-injection of 4-AP and PFT in SMA mice (from birth through death) and observed full correction of the synaptic response. These results suggest that multiple interventions can come together to counteract different aspects of SMA pathophysiology.  

Putting it all together 

Gene therapies are promising interventions to treat SMA, and the Thomsen et al. study showed that this approach can change the patients’ phenotype and increase expression of SMN in motor neurons. Most importantly, the treatment increased neuronal viability and helped patients reach important motor milestones. As research and clinical management of SMA continues to evolve, the development of adjunctive therapies may significantly improve patients’ quality of life. Data from Simon et al. exemplifies how targeting neuronal activity at the NMJ and the p53 pathway can improve functional outcomes. Tackling different aspects of the SMA pathophysiology can help the scientific and medical communities reach the long-term pursuit of finding a cure for SMA.  

Vector Laboratories is proud to empower scientists to move knowledge forward. Check out our learning resources and reach out to our team of experts if you need technical assistance with your experiment and reagent selection.   

References  

1. Schorling DC, et al. 2020. Advances in Treatment of Spinal Muscular Atrophy – New Phenotypes, New Challenges, New Implications for Care. Journal of Neuromuscular Diseases.
2. Chaytow H, et al. 2021. Spinal Muscular Atrophy: From Approved Therapies to Future Therapeutic Targets for Personalized Medicine. Cell Reports Medicine.
3. Mendell JR, et al. 2017. Single-Dose Gene-Replacement Therapy for Spinal Muscular Atrophy. The New England Journal of Medicine.
4. Day JW, et al. 2021. Onasemnogene Abeparvovec Gene Therapy for Symptomatic Infantile-Onset Spinal Muscular Atrophy in Patients with Two Copies of SMN2 (STR1VE): An Open-Label, Single-Arm, Multicentre, Phase 3 Trial. The Lancet Neurology.
5. Thomsen G, et al. 2021. Biodistribution of Onasemnogene Abeparvovec DNA, mRNA and SMN Protein in Human Tissue. Nature Medicine.
6. Simon CM, et al. 2021. Chronic Pharmacological Increase of Neuronal Activity Improves Sensory-Motor Dysfunction in Spinal Muscular Atrophy Mice. The Journal of Neuroscience.
7. Le TT, et al. 2005. SMNΔ7, The Major Product of the Centromeric Survival Motor Neuron (SMN2) Gene, Extends Survival in Mice with Spinal Muscular Atrophy and Associates with Full-Length SMN. Human Molecular Genetics.
8. Ling KKY, et al. 2010. Synaptic Defects in the Spinal and Neuromuscular Circuitry in a Mouse Model of Spinal Muscular Atrophy. PLOS ONE.
9. Mentis GZ, et al. 2011. Early Functional Impairment of Sensory-Motor Connectivity in a Mouse Model of Spinal Muscular Atrophy. Neuron.
10. Ruiz R, et al. 2010. Altered Intracellular Ca2+ Homeostasis in Nerve Terminals of Severe Spinal Muscular Atrophy Mice. The Journal of Neuroscience.
11. Chung L. 2015. A Brief Introduction to the Transduction of Neural Activity into Fos Signal. Development & Reproduction.
12. Simon CM, et al. 2017. Converging Mechanisms of p53 Activation Drive Motor Neuron Degeneration in Spinal Muscular Atrophy. Cell Reports.