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A War of Multiple Fronts: How to Fight Duchenne
By Alex Neupauer, Genetics and Genomics, ’23
Author’s Note: As a Genetics and Genomics major and a person with Duchenne muscular dystrophy (DMD), I was compelled to write a review on how to alleviate the suffering imposed by this devastating genetic disease. I consulted various scholarly articles and interviewed five experts on DMD. Approaches to improve patient outcomes will involve a mixture of researching cures and improving the care of patients’ symptoms. While we may be far away from truly curing DMD, we are not currently powerless against it. With this article, I hope to promote awareness of DMD among both scientists and the public, as the DMD community relies on outside support to improve patient outcomes.
Abstract
Duchenne muscular dystrophy (DMD) is a devastating disease resulting in muscle degradation. DMD results from mutations to the dystrophin gene that impair the function of the dystrophin protein, an important structural component of muscle tissues. Individuals with the disease suffer from the impacts of weakened muscles on skeletal, circulatory, and pulmonary systems, often shortening their lifespan. The main solution consists of restoring dystrophin expression in cells. CRISPR/cas9 and gene replacement therapy can in theory restore dystrophin expression, while other methods can restore some of its function. To implement CRISPR or gene therapy as cures, researchers must figure out how to deliver them safely and effectively to cells. They must also improve and expand treatments already on the market or on trial to target a wider variety of DMD patients. Exon-skipping therapies only exist for skipping the exons most often implicated in DMD. And nonsense mutation readthrough appears to work better in theory than practice. Implementing and improving methods of dystrophin restoration will also rely on better modeling of DMD and more basic research in molecular and cellular biology. Improved care for the symptoms of DMD is also vital while researchers find and develop cures. To better care for patients’ DMD-related complications, we must create better standards of comprehensive care and facilitate their access to it. Finally, education about DMD is key. Public education will lead to increased funding, allowing for more necessary research. Education will also promote parents’ awareness of screening for DMD and clarify complex care considerations for patients and their families, making quality care easier to secure.
Background
DMD results from the lack of a functional gene encoding dystrophin. Muscle tissues must constantly bear the force of contraction and need proteins like dystrophin to reinforce their strength. Dystrophin ensures muscle fibers and their membranes are not damaged during contraction [1]. Specifically, it links actin filaments inside muscle cells to membrane proteins, which in turn link the membrane to the extracellular matrix [2]. Without dystrophin, actin filaments lack a stable connection to the extracellular matrix, resulting in muscle cell damage.
Dystrophin attaches f-actin to membrane-bound proteins on the muscle cell membrane (sarcolemma). These membrane proteins attach to the extracellular matrix. Without dystrophin, this membrane-bound complex is abolished and f-actin is not anchored to the extracellular matrix. Image from Mbakam et al [1].
The cell damage induces cellular stress, inflammation, and eventual cell death [3], and improper muscle function ensues. As a consequence, individuals with this disease typically become wheelchair-bound in their mid-teens. The lessened use of skeletal muscles results in increased bone fragility and the development of contractures [4] – permanent stiffening of the joints. People with DMD also develop complications in cardiac and respiratory muscles, the most serious complications as a result of the disease [1]. As such, DMD has a negative impact on lifespan and quality of life. And there is no present cure for the disease.
In addition to the lack of a cure, patients often suffer from inadequate care of their symptoms. As the disease impacts patients beginning from a young age, critical care decisions are those of their parents. Despite their best intentions, patients’ families sometimes make choices that negatively impact their outcomes. For example, families refuse steroid treatments, which do not cure DMD but significantly improve patient outcomes. Jessica A. Guzman, an RN for the pediatric neuromuscular clinic at Lucile Packard Children’s Hospital, laments that parents may hold off on steroids out of fear of relatively minor side effects such as shortened stature or in anticipation of a ‘miracle drug’ [5]. Parents may also fail to work through the labyrinth of caring for the health of their child, as the disease impacts many body systems, requiring the attention of many specialist doctors. Scheduling appointments with cardiologists, pulmonologists, orthopedic doctors, and more can be overwhelming. Parents’ uninformed decisions and difficulty navigating the needs of DMD demonstrate the need for increased education on DMD and more support for patients from the medical community.
Stopping the suffering inflicted by DMD has medical, scientific, and social barriers. And it leaves behind it a path of destruction that humanity should not accept. The best approach to end the devastation of DMD consists of researching and implementing methods to restore dystrophin expression to all muscle tissues while improving the care of patients’ symptoms and overall health, employing public education, better models, and basic research to overcome implementation challenges.
Restoring Dystrophin Expression
One of the best solutions is to tackle the problem at the root: the lack of dystrophin protein. There are several approaches to restore the expression of this essential protein: CRISPR/cas9, gene replacement therapy, exon-skipping, and post-transcriptional methods.
Gene Replacement Therapy
One of the most noteworthy challenges in treating or curing DMD relates to the fact that many types of mutations can lead to dysfunction of the dystrophin gene. Patients can have deleted or duplicated exons or point mutations of a single nucleotide [1]. And there is much variability with respect to which exons are affected or which nucleotides are mutated. Gene replacement therapy sidesteps the need for mutation-specific cures by providing all cells with a brand-new copy of the dystrophin gene. Adeno-associated viruses (AAVs) can deliver the replacement dystrophin gene. However, the dystrophin gene is over 2 million bases while the capacity of AAVs is only around 4,700 bases [2]. Micro-dystrophin overcomes this capacity issue, encoding a 1,001 amino acid long protein compared to the 3,684 amino acid long wild-type protein [2]. Carly Siskind, MS, CGC from Stanford Health Care, believes the approach could be helpful, so long as all necessary parts of the protein are encoded by the miniature gene [6]. However, micro-dystrophin does not replace the original protein, which is much longer. In other words, micro-dystrophin appears to solve the problem as a mediocre substitute, which poses the question of whether this mechanism can wholly cure DMD or not.
Furthermore, Claudia Senesac, PT, PhD, PCS from the University of Florida, laments that gene replacement therapy does not appear to last forever, requiring eventual redosing [7]. Unless gene therapy targets satellite cells, the therapy can be lost as muscle cells are replaced. Muscle tissues naturally have turnover rates, which are elevated in the context of gene therapy, as it does not tend to remedy 100 percent of all muscle cells [2]. Satellite cells divide to replace damaged muscle cells, so they must also contain functional dystrophin genes to ensure replaced muscle cells also have a functional copy of the gene. Unfortunately, AAVs do not target satellite cells very effectively [2]. Gene replacement therapy avoids having to consider a patient’s particular mutation, and thus sounds like an excellent solution. However, gene replacement therapy in its current form does not constitute a cure. To make gene therapy a cure, we must develop delivery systems of higher capacity that target a wide array of muscle cell types and create longer-lasting therapies.
CRISPR/cas9
The mechanism of CRISPR/cas9 originates as a bacterial defense against viruses. The CRISPR array locus contains a catalog of sequence fragments from previously infecting viruses. These fragments are known as spacer sequences, which alternate with invariable repeats: spacer, repeat, spacer, repeat, etc. When a novel virus infects bacteria, they sequester fragments of viral DNA and insert them into their CRISPR array locus. When the virus infects again, bacteria transcribe their entire CRISPR array. The mRNA of each spacer sequence is cleaved from the array and loaded onto a cas9 protein. The cas9-RNA complexes containing RNA complementary to segments of the invading viral DNA bind to the viral DNA. Then cas9 cuts at the binding site. Thus, the CRISPR system has high specificity with regard to where it cuts. In the lab, researchers can create their own short RNA sequences called small guide RNA (sgRNA) to guide cas9 to specific sites in DNA.
Mechanism of CRISPR in a bacterium. Viral DNA sequences are saved in the CRISPR array locus and transcribed during future infection to target cas9 to cut viral DNA. Image from “A Tool for Genome Editing: CRISPR-Cas9,” BioRender in collaboration with the Doudna Lab at UC Berkeley.
Researchers have adapted the system to accomplish a variety of functions that may be applicable to curing/treating DMD. Three useful applications are exon knock-in, base editing, and prime editing. Exon knock-in consists of CRISPR cutting the DNA between exons and inserting the missing exon, both restoring lost information and the reading frame [2]. Base editing uses enzymes that chemically convert one base into another. These enzymes are attached to a CRISPR system to guide the modifications to specific nucleotides [1]. Prime editing uses reverse transcriptase, guided by CRISPR, to replace a short segment of DNA with new DNA synthesized from an RNA template [1]. As these templates can contain different, extra, or missing nucleotides relative to the original DNA sequence, prime editing can change, insert, or delete particular nucleotides at particular sites. Taken together, prime and base editing can resolve point mutations. Thus, the diversity of CRISPR editing methods fits well with the diversity of mutations causing DMD. One big issue remains: targeting every single muscle cell with this treatment.
AAVs can deliver the materials necessary for the cell to complete CRISPR editing [2]. However, this delivery mechanism would succumb to the same issues of targeting satellite cells. Lipid nanoparticles may be another possibility for delivery. Together, cas9 (cationic) and sgRNA (anionic) form an anionic ribonucleoprotein (RNP) complex, which is placed inside a cationic lipid nanoparticle [2]. The RNP enters the cell via endocytosis [2], the fusion of the lipid nanoparticle envelope with the phospholipid membrane. It could be a promising avenue given the success of COVID-19 vaccines designed with lipid nanoparticles. Unfortunately, CRISPR also must overcome the challenge of off-target cuts. Permanent changes to DNA can be dangerous if done incorrectly, as the cell’s genome is forever changed. Jacinda Sampson, MD, PhD, adds that CRISPR can now be modified to target mRNA instead [4]. Thus, permanently altering the genome is no longer a concern. Collectively, all experts interviewed express hope of CRISPR as a future treatment option but recognize the aforementioned challenges in achieving that goal [4, 5, 6, 7, 8].
CRISPR gene editing is an exciting possibility for a future cure. To use CRISPR as a cure, we must overcome its delivery challenges and investigate its safety in humans. Additionally, researchers should further investigate RNA CRISPR and lipid nanoparticle delivery as potential cures.
Small Molecules and Exon Skipping
There are other possible methods to restore dystrophin expression that do not involve changing the gene or delivering new copies. Rather, they work with the cell to use the mutated code in a way that allows for the production of dystrophin. One such approach uses small molecules to induce ribosomes to read through a nonsense mutation in dystrophin mRNA. Govardhanagiri et al define small molecules as molecules less than 900 Da, including drugs and biological molecules not including proteins, nucleic acids, or polysaccharides [9]. The fact that cells selectively degrade transcripts with premature stops suggests that premature and normal translation termination may have different mechanisms. Aminoglycosides have been able to promote nonsense mutation readthrough but are toxic after continued use [10]. Pharmaceutical company PTC Therapeutics used high throughput screens to identify nontoxic compounds that promote readthrough of exclusively premature stops in mammalian cells and found ataluren as their top candidate [10].
Chemical structure of ataluren.
While ataluren restored some fully functional dystrophin expression in mouse models, only a small proportion of patients in their study showed increases in dystrophin expression [10]. In theory, the right small molecule drug can allow ribosomes to skip over premature stops to make full length, fully functional dystrophin, halting disease progression. It seems that in practice, this reality does not yet exist. Dr. Sampson hopes that small molecule treatments will improve in the future [4]. However, point mutations like premature stops only represent a fraction of all patients [1].
Another method uses antisense oligonucleotides (AONs) to skip over problematic exons [11]. During splicing, exons must contain an exonic splicing enhancer (ESE) to be retained in the mRNA transcript. ESEs recruit splicing factors that ensure exon inclusion. AONs complementary to an ESE bind to the ESE, abolishing the binding of splicing factors and causing the exon to be spliced out [11]. Exon-skipping may partially restore dystrophin expression in a variety of contexts. Exons could have problematic point mutations that need to be skipped over. Or, an exon deletion could disrupt the reading frame, such that skipping neighboring exons would restore the reading frame. However, exon skipping produces shortened dystrophin, which significantly improves but cannot eliminate the disease phenotype entirely. Furthermore, because each exon is unique, a different treatment must be developed for each specific exon to be skipped. Some already exist on the market, but only for the most commonly problematic exons.
However, AON exon-skipping and nonsense mutation readthrough have already emerged in clinical trials or on the market, making them a more present solution than gene therapy or CRISPR. Nonsense mutation readthrough must improve and exon-skipping treatments must come to include patients with a larger variety of mutations. Exon-skipping remains a good way to mitigate the effects of DMD while more effective treatments are developed. Additionally, if nonsense mutation readthrough therapies become effective, they will be complete cures in their own right.
CRISPR/cas9, gene replacement therapy, and nonsense mutation readthrough can restore fully functional dystrophin, but require much development before patients can use them. Exon-skipping therapies are more readily available but do not wholly cure DMD. Restoring dystrophin attacks the problem at the source, making it an integral part of the fight against DMD.
Improved Care
Even without a present cure, we still have power against the disease. Patients can fight back with quality health care targeting the damage inflicted by DMD. Seeing DMD patients daily as a nurse, Guzman stresses the importance of comprehensive health care:
While research is crucial, we must not forget that while studies are ongoing, [patients] will get weaker. We need to make sure that the patient is well cared for in [their] cardiac function […] There is quite a difference between our patients that have parents championing them with good care and follow up, vs. patients that are not being compliant with care recommendations [5].
Guzman urges that while a cure remains on the minds of most patients and their families, they must not forget to care for the symptoms of DMD in the present. Furthermore, the fact that patients with good care fare much better than those without it demonstrates the importance of quality care. Similarly, Dr. Sampson notes the importance of monitoring patients’ bone and pulmonary health and preventing contractures [4]. Unfortunately, scheduling all these appointments with various specialists is difficult and overwhelming for patients and their families. Additionally, many DMD clinics do not have all specialists present at once [5]. DMD patients need more standardized care programs, which integrate multiple specialists into a single check-up. Patients would benefit from a healthcare liaison who helps them comply with care standards and schedule appointments, especially if clinics cannot schedule all specialists into one appointment.
But care encompasses much more than tending to physical health. If our culture becomes more supportive of folks with disabilities, the outcome for DMD patients will improve. While this article focuses on DMD, we must remember that social justice for folks with disabilities at large remains an important goal to improve the lives of countless people, not just those with DMD. The motivation for cures of serious diseases must originate from a desire to reduce suffering, rather than a desire to remedy resulting inabilities out of the belief that they reduce the value of the people who have them. Neither should we accept the personal ‘shortcomings’ of folks with disabilities as the source of their barriers; social attitudes and infrastructure are the real shortcomings we must resolve. Siskind argues that we “need to have a better society for people who are differently-abled,” filled with improved infrastructure, more considerations, and better mindsets for those using wheelchairs [6]. Alleviating the challenges of DMD in the present includes lessening the burden of wheelchair use. If we ease the daily lives of those with disabilities and provide infrastructure that expands their freedom, their quality of life will improve. Even if supporting the disability-related needs of DMD patients does not directly benefit their physical health, it improves their emotional state, which in turn improves physical well-being. If we look after the whole person – mind, body, and spirit – we will reduce much suffering from DMD right now.
Additional Considerations
Addressing Scientific Gaps in Knowledge
Improved modeling of the disease will help tackle the challenges of implementing new biological discoveries as treatments and better care standards. Human induced pluripotent stem cells (iPSCs) provide a more accurate cellular model in which to study DMD than mouse models. iPSCs are formed by extracting a patient’s cells and converting them to stem cells [2]. From there, they could be turned into muscle cells to study DMD. Vera et al describe one study, which found an herbal compound that reduced oxidative stress in DMD heart cells derived from iPSCs [3]. Thus, iPSCs are already clarifying disease processes and elucidating treatments to alleviate the damage caused by DMD. Artificial intelligence can improve conceptual models of DMD. In particular, natural language processing (NLP), can comb through existing literature to find possible treatment combinations or characterize processes of DMD that humans cannot [3]. Thus, AI could find new information about DMD within existing studies and published work. Even modeling at the stage of clinical trials is important. According to a doctorate of neurology from Stanford University who prefers to remain unnamed, “improved genotype:phenotype information before and after various treatments will provide real world data that will clarify the disease process, response to treatment and cause of unmet needs [8].” More modeling of the disease will reveal more about the processes of and players implicated in DMD. Thus we will be able to better predict what we need to remedy and how diseased muscle cells will respond to a given treatment. When improved models fill gaps in knowledge, solutions to the implementation of treatments become more clear. In the case of iPSCs, patients can even have personalized models, allowing them to receive more targeted treatments. Furthermore, these increases in knowledge will inspire brand new treatment approaches in addition to perfecting current ones for clinical implementation.
Basic research improves the general understanding of biology, eventually filling gaps in knowledge necessary to implement CRISPR, gene replacement therapy, and nonsense mutation read-through as cures. The anonymous researcher expressed that studying molecular and cellular biology, particularly in diseased cells, shows promise in the fight to cure DMD [8]. For example, improved knowledge of cell biology can better illuminate how cells import materials from their surroundings and respond to exogenous DNA. Such knowledge could lead to more effective deliveries to muscle cells and reveal why replacement genes in gene therapy lose effectiveness over time. We must also increase our knowledge specifically on the cell types that will be the target of cures. Even basic research in seemingly distant fields could bring forth unforeseen possibilities. For example, CRISPR/cas9 would not exist without having studied bacterial immunity. And computer science led to AI and NLP, which may one day lead the fight against DMD. Basic research provides the raw materials from which new cures are built.
Public Education and Outreach
Finally, public education will be necessary to both secure proper funding for research and promote screening to limit the disease’s toll. Dr. Senesac calls for public education to increase awareness of the disease [7]. Although the disease is devastating, the public will stand still until they become aware of its existence. As a small community, the DMD community can only make progress with the support of the public. Without knowledge, the public cannot provide support for movements, especially those securing more funding from corporations and governments. Three of five expert respondents directly stated that more money was needed for research [5, 7, 8]. Given that these respondents have direct ties to research, their personal opinion that more funding is needed speaks volumes. A better-educated public also results in parents who are more aware of screening options. Nurse Guzman explains that early screening can “not only identify the child that is affected, and [allow families to] start making interventions early, but can… have an impact on family planning [5].” She recalls that some families discovered their status as carriers too late, having multiple children with DMD. Had they known of their first kid’s diagnosis earlier, they would have not had more kids or screened embryos [5]. Educating parents or prospective parents on screening expands the ways they can look out for the health of their kids. An old adage suggests knowledge is power. In the case of DMD, education is an integral weapon in the fight.
Conclusion
Duchenne muscular dystrophy is responsible for immense suffering, but we have tools with which to fight the disease: research to restore dystrophin expression, improved care, improved modeling, and public education. There are various promising approaches to treatments requiring varying amounts of development to become a reality. For example, patients are already using exon-skipping therapies, while CRISPR requires much more research to be safely applied to humans. In addition to attacking the root cause of DMD, caring for the whole person results in better health and improved quality of life in the face of devastation. Basic research and modeling will close the necessary gaps in biology to develop improved treatments and care regimens. Finally, public education brings awareness to the issue to instill action against DMD, potentially overcoming the issue of funding. We have many tools to fight DMD, and winning the battle requires the use of all of them. Likewise, genetic counselor Siskind remarks that “we are a long way from truly curing DMD, and people with DMD need resources from many different avenues [6].”
In reality, the problem is not DMD alone. The approaches outlined here could apply to other monogenic diseases. But the issue of disease in general extends far beyond science. In addition to being a biological issue, disease is a social, economic, and political issue. We cannot act on any disease without the support of entire societies worldwide. Fighting disease requires many people working together to not only find a cure but to care for those ailing from them in the present. Science is a necessary component of fighting disease, but it is not sufficient. When we fight disease, we fight with our heads and our hearts.
References:
- Mbakam CH, Lamothe G, Tremblay G, Tremblay JP. 2022. CRISPR-Cas9 Gene Therapy for Duchenne Muscular Dystrophy. Neurotherapeutics [Internet]. 19(3):931-941. doi:10.1007/s13311-022-01197-9
- Min Y, Bassel-Duby R, Olson EN. 2019. CRISPR Correction of Duchenne Muscular Dystrophy. Annu Rev Med [Internet]. 70(1):239-255. doi:10.1146/annurev-med-081117-010451
- Vera CD, Zhang A, Pang PD, Wu JC. 2022. Treating Duchenne Muscular Dystrophy: The Promise of Stem Cells, Artificial Intelligence, and Multi-Omics. Front Cardiovasc Med [Internet]. 9:851491. doi:10.3389/fcvm.2022.851491
- Sampson, Jacinda, MD, PhD. Interview conducted by Alex Neupauer. May 13, 2022.
- Guzman, Jessica A., RN. Interview conducted by Alex Neupauer. May 13, 2022.
- Siskind, Carly, MS, CGC. Interview conducted by Alex Neupauer. May 13, 2022.
- Senesac, Claudia, PT, PhD, PCS. Interview conducted by Alex Neupauer. May 13, 2022.
- Anonymous. Interview conducted by Alex Neupauer. May 13, 2022.
- Govardhanagiri S, Bethi S, Nagaraju PG. 2019. “Small Molecules and Pancreatic Cancer Trials and Troubles.” In Breaking Tolerance to Pancreatic Cancer Unresponsiveness to Chemotherapy, edited by Ganji P. Nagaraju, 117-131. Elsevier. doi:10.1016/C2018-0-02682-1
- Peltz SW, Morsy M, Welch EM, Jacobson A. 2013. Ataluren as an agent for therapeutic nonsense suppression. Annu Rev Med [Internet]. 64:407-425. doi:10.1146/annurev-med-120611-144851
- Aartsma-Rus A, van Ommen GJ. 2007. Antisense-mediated exon skipping: a versatile tool with therapeutic and research applications. RNA [Internet]. 13(10): 1609-1624. doi:10.1261/rna.653607
The Gut Microbiome and Obesity
By Lazer Introlegator, Neurobiology, Physiology, and Behavior, ’23
Author’s Note: Ever since I learned about the existence of the microbiome, I have been fascinated. When Dr. Brenda Rinard assigned my UWP102B class (Writing in the Biological Sciences) the task of writing a formal scientific literature review on a topic of our choosing, I knew that the assignment would be the perfect opportunity to delve deeper into understanding the role of the gut microbiome, specifically the gut microbiome’s role in influencing obesity. I chose the topic of obesity specifically because in previous social science classes, I learned about some of the socio-economic reasons for widespread obesity, and I wanted to learn the perspective of the medical community and how science is progressing in its understanding of the gut microbiome’s influence on obesity. My hope is that after reading this review, the reader will be intrigued to learn more about the amazing role the gut microbiome plays in our body.
Introduction
Roughly 30% of people worldwide are overweight or obese [1]. In the past four decades, obesity rates have nearly doubled in over seventy countries [1]. Overweight and obese individuals are at higher risk for various illnesses such as type 2 diabetes and heart disease. A healthy diet and exercise are known methods to combat and prevent obesity [2]. Unfortunately, many people with low income in the United States do not have access to a healthy diet [3].
Another major factor known to play a role in a person’s weight is their gut microbiome. The gut microbiome refers to the trillions of bacteria, fungi, and viruses that live within the guts of animals. These microscopic organisms help their hosts digest food, modify gene expression, fight off foreign infections, and more. Understanding how bacteria within the gut microbiome plays a role in obesity will allow us to manipulate the gut microbiome and combat obesity.
In the growing field of gut microbiome research, scientists have been looking into how the metabolite butyrate, a gut bacteria byproduct, plays a role in obesity. There is conflicting research regarding whether butyrate plays a beneficial or harmful role within the gut microbiome. This review examines how butyrate affects the gut microbiome, the role of the bacterium Lactobacillus sakei (L. sakei) ADM14 in combating obesity, how diet and exercise play an integral role in combating or causing obesity, and whether fecal microbiota transplantation may be used as a therapy to combat obesity.
Altering the gut microbiome
Time Frame for Change
Understanding how long altering the gut microbiome takes is the first step in understanding how to manipulate the gut microbiome. Studies have shown that the gut microbiome can change rapidly even after one day of a changed diet [4]. In one study conducted by David et al., people were fed either a plant- or animal-based diet, resulting in the rapid modification of their gut microbiome. The different diets resulted in different species of bacteria becoming more prominent in the participants’ gut microbiome. David et al. were surprised by how quickly the gut microbiome of each of the participants began to resemble the known gut microbiomes of either herbivores or carnivores [4]. “David et al. theorized that the reason the human gut microbiome can change rapidly based on diet is due to human evolution requiring our ancestors’ bodies to quickly adapt to any food source available [4].” This leads to the possibility that the gut microbiome can be rapidly manipulated. Dietary changes, medications, and probiotics can potentially be used to quickly alter the gut microbiome to combat obesity and improve gut health.
Composition
The gut microbiome has various bacteria that play a role in combating or causing obesity. A study by Gao et al. used 192 people of varying weights to show a correlation between certain gut bacteria and obesity [5]. The study found that in all the participants, Bacteroidetes and Firmicutes were the largest phyla by number of bacteria within the microbiome. All the participants were also found to have a similar total number of bacteria present in their gut. However, the ratio of the different types of bacteria in each group differed. Obese participants were found to have the least diverse microbiomes; they had a greater amount of the phylum Proteobacteria present than non-obese participants [5]. At the genus level, the study found proportional differences amongst the groups of bacteria present in their gut microbiomes. The Pseudomonas and Fusobacterium were two genera found in small proportion amongst participants at a healthy weight and in much larger abundance amongst the obese participants. The absence of these genera was theorized to be associated with a healthy weight [5].
A large study by Peters et al. identified which bacteria need more evidence to show their connection to obesity [6]. This study researched whether the diversity and composition of the human gut microbiome in American adults could be associated with obesity. The study analyzed the microbiome composition of fecal samples from 599 individuals split into two separate populations. 451 people were in Minnesota and were between the ages of 50 – 75, and 176 people were in New York and were between the ages of 29 – 86. The study verified that the gut microbiome of obese people compared to people at a healthy weight differed in composition. Similar to the study conducted by Gao et al., the study by Peters et al. verified that the phyla of Bacteroidetes and Firmicutes were the largest groups of bacteria within the microbiome, but they did not find a correlation between obesity and the Firmicutes to Bacteroidetes phyla ratio [6].
However, Peters et al. did find a correlation between certain classes of bacteria in the Firmicutes phylum and obesity [6]. The classes of bacteria associated with obesity were the Bacilli class and the Clostridia class. Obese individuals were found to have higher levels of the Bacilli class and lower levels of the Clostridia class compared to the healthy weight individuals. Overweight people showed similar trends in their gut microbiome as the obese individuals. Additionally, the bacteria that were found in lower abundance in obese people and higher abundance in healthy weight individuals were found to be associated with the beneficial butyrate metabolism (decreasing the amount of butyrate excreted in fecal matter) [6]. This means obese people in the study were less likely to benefit from butyrate metabolism. Butyrate metabolism promotes increased gut health and potentially plays a role in preventing and combating obesity. While Peters et al. identified bacteria that may play a role in causing or preventing obesity in humans, the way these bacteria prevent or cause obesity is not yet understood.
The Role of Butyrate
The byproducts of the bacteria in the gut microbiome can play a role in obesity as well. One specific type of bacteria product, or metabolite, is the short-chain fatty acids (SCFAs). Many obesity studies have focused on an SCFA called butyrate. Nandy et al. researched whether there was a correlation between the metabolites of the various bacteria in the gut microbiome and obesity [7]. This study analyzed stool samples from 170 two-year-old children. To best determine which metabolites were involved in weight determination, Nandy et al. tracked 20 independent variables that could influence the outcome (such as maternal smoking and diet). The only metabolite that showed a significant influence on weight was the SCFA butyrate. The children who were overweight or obese showed much higher levels of butyrate in their stool samples compared to the children that were of healthy weight or underweight. This study is important because it provides insight into how butyrate may play a role in child weight gain [7]. This research provides a foundation for future studies investigating the influence other metabolites may have on human health. Additionally, this study can help the scientific and medical communities combat obesity by predicting which children may become obese later in life and implementing preventive measures.
Another study by De la Cuesta-Zuluaga et al. investigated whether there was any correlation between the amount of fecal SCFAs to either gut structure or obesity [8]. De la Cuesta-Zulanga et al. used fecal samples from 441 volunteers to determine their microbiome composition and SCFA concentration. Additional data was collected from each volunteer detailing their daily diet and exercise regimen. This research showed that those with a higher butyrate concentration in their fecal samples were more likely to be male, have a lot of fiber in their diet, and be obese. High butyrate concentrations, along with other SCFAs, also showed a correlation with having a less diverse gut microbiome. The study also found that high butyrate concentrations were shown to have a correlation with poor gut structure [8]. Poor gut structure in this context refers to gut permeability, also known as leaky gut. “Leaky gut occurs when pathogens are not successfully prevented from entering the gut microbiome where they can then cause an imbalance of bacteria in the gut microbiome.” De la Cuesta-Zuluaga et al. found that volunteers with low fecal SCFA concentrations were more likely to be female and at a healthy weight. The study also showed that lower butyrate levels were associated with a higher level of Bacteroides in the human gut microbiome [8]. The mechanisms of butyrate within the gut are not yet understood and require further research.
Therapies
Probiotics
Ingesting live bacteria (probiotics) is a potential therapy to alter the gut microbiome. Won et al. used 24 mice to test the potential of the probiotic Lactobacillus sakei (L. sakei) ADM14 in preventing obesity [9]. Won et al. isolated the L. sakei ADM14 from kimchi, a Korean dish made from fermented vegetables. The bacterium was then grown in a lab to be fed to certain mice over a ten-week period. Four groups of six mice each were made at random. Two groups fed a normal diet were labeled ND and NDA and two groups fed a high-fat diet were labeled HD and HDA. Both the NDA group and the HDA group had the L. sakei ADM14 included in their diet. Around five weeks into the experiment, the HDA group began to weigh significantly less than the HD group. By the end of the experiment, Won et al. calculated that the HD group had gained over 25% more weight than the HDA group. Additionally, the HD group had a significant increase in blood cholesterol and blood glucose levels compared to the ND and HDA groups [9].
Won et al. also found that the ratio of Bacteroidetes (a group of bacteria that assist in the breakdown of carbohydrates and certain sugars) was much lower in the HD group than the other groups [9]. Bacteroidetes produce short-chain fatty acids (SCFAs) which greatly help maintain gut health and are commonly found in the microbiome of lean individuals. The HD group was found to be lacking in SCFAs. The NDA group showed similar findings to the ND group. Won et al. took these findings to suggest that L. sakei ADM14 only plays a role when there is a high-fat intake occurring in an individual [9]. The implications of this study are that L. sakei ADM14 has an impact on the microbiome and obesity. This study suggests that L. sakei ADM14 can encourage healthy bacterial growth, and prevent weight gain from a high-fat diet in mice. Won et al. believe further studies on L. sakei ADM14 can provide the medical field with probiotics that can help combat obesity [9]. More studies with larger data sets must be done to further understand how L. sakei ADM14 affects the gut microbiome in humans.
Diet and Exercise
A healthy diet and physical activity may be enough to maintain a healthy gut microbiome and prevent obesity [2,10]. A study conducted by Wang et al. with mice tested whether moderate treadmill exercise had an effect on the gut microbiome and barrier [2]. The gut barrier prevents pathogens from entering the gut microbiome and causing an increase in detrimental bacteria and a decrease in beneficial bacteria. Wang et al. randomly divided 24 mice into four groups of six. The first group (SD + Sed) was fed a standard diet with no exercise. The second group (SD + Exe) was fed a standard diet combined with exercise. The third group (HFD + Sed) was fed a high-fat diet with no exercise. The fourth group (HFD + Exe) was fed a high-fat diet combined with exercise. The exercise groups ran on a treadmill for 45 minutes, five days a week, for twelve consecutive weeks. Researchers collected blood, fecal matter, and bodyweight levels each week. The two groups fed a standard diet had relatively low weights during the twelve weeks. The HFD + Sed saw the mice double their body weight. Wang et al. found that the high-fat diet with exercise group had a more diverse gut microbiome than the high-fat diet group with no exercise [2].
Both the exercise groups were found to have altered their microbial structure compared to the non-exercise groups. Exercise was also found to increase the amount of Verrucomicrobia in the gut microbiome which a high-fat diet typically reduces [2]. This research also found that exercise helped bring bacteria to a healthy concentration even though the high-fat diet caused an imbalance in the microbiome. An additional finding was that a high-fat diet caused the gut to have less structural stability and an increased chance of foreign bacteria and pathogens invading the gut microbiome. The study also found that the high-fat diet with exercise group showed much more order and structural integrity of their guts compared to the high-fat diet group with no exercise [2]. This study suggests that those with unhealthy diets can counteract some of the negative influences caused by a high-fat diet by beneficially altering their gut microbiome through exercise
Fecal Microbiota Transplantation
A study by Lai et al. gave mice fecal microbiota transplantations (FMT) [10]. FMT is a process where fecal matter with the desired gut bacteria is collected from one individual and put into another, typically via colonoscopy or enema. Lai et al. wanted to see if and how FMT from mice with a healthy gut microbiome to obese mice would affect the gut microbiome of the recipient obese mice [10]. The study took 47 five-week-old mice and randomly split them up into seven groups that differed in diet and exercise regimen. Antibiotics were given to the groups undergoing FMT for several days before receiving FMT to prepare them for the gut microbiome recolonization process. The recipients were given the FMT 5 days a week from week 12 until week 24 [10]. After two of the non-exercise groups received FMT from groups that did exercise, their gut microbiomes became similar to the group which had a high-fat diet and exercised regularly. Lai et al. understood this finding to imply that the recipient’s diet affects which microbes can colonize their gut microbiome after FMT [10]. This study is important because it shows that FMT can transfer the benefits of diet and exercise to mice that have poor diet and no exercise. This study complements previous studies that show that diet and exercise can beneficially alter gut microbiome composition [10]. Using the results of this study for future studies and eventually human trials can potentially help combat and prevent obesity in humans. However, the methods of FMT performed in this mouse trial are not practical in human trials yet, so future human trials will need to make adjustments to the FMT procedure.
Conclusion
Obesity is a serious health concern for people worldwide. Certain bacteria are associated with obesity and gut health. The role of bacteria and their products are yet to be fully understood, but methods of altering the gut microbiome have come a long way. Therapies are being developed such as exercise, improved diet, probiotics, and fecal microbiota transplantation to combat obesity. “Although a healthy diet is shown to have the most impact on maintaining a healthy gut microbiome, exercise is currently the most accessible and beneficial therapy in maintaining gut health and combating obesity.” The mechanism by which bacteria and their products affect obesity and the gut must be better understood, and therapy trials must move from mice to humans.
References:
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- Wang J, Zhang Q, Xia J, Sun H. 2022. Moderate Treadmill Exercise Modulates Gut Microbiota and Improves Intestinal Barrier in High-Fat-Diet-Induced Obese Mice via the AMPK/CDX2 Signaling Pathway. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 15:209–223.
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The Effects of Ozone on Plant-Pollinator Interactions
By Hanna Francis, Biological Sciences ’22
Author’s Note: I grew interested in plants through botany and plant biochemistry courses at UC Davis and learned about insects while volunteering at the Bohart Museum of Entomology on campus. After taking a course about the toxicology of air pollutants, which focused primarily on human health outcomes, I began to wonder how air pollution affects organisms other than ourselves. In investigating current research at the intersection of these three things– plants, insects, and air pollution– I found that plant-pollinator interactions are affected by ozone pollution in a variety of ways, some of which may be harmful to agriculture and biodiversity. I hope that readers will become aware of just how complex the effects of pollution are on the natural world. The paper may at first seem bleak, however, there must always be hope. I truly believe that research like this will help inform regulatory standards for air pollution that will protect both humans and our environment from damage in the future.
Introduction:
The concentration of ozone (O3) in the earth’s atmosphere has increased dramatically due to industrialization and is predicted to increase by two- to four-fold over the next twenty years [1,2]. Human activity, especially in the form of transportation and manufacturing, emits pollutants such as nitrogen oxides (NOx), which react with oxygen and UV light in the atmosphere to form ozone [3,4]. Ozone is a highly reactive gas known to lead to human lung diseases such as asthma [5], but its effects on other organisms are not as well understood.
Pollination– a process vital to agriculture– is reliant upon insects and plants, so it is crucial to understand the effects of ozone pollution on this process [6]. Insect pollination is necessary for over 80% of global crops [6]. In addition to agricultural plants, wild plant species have also been shown to be sensitive to ozone and studies have found ozone to be associated with a loss in wild species diversity [7]. Recent research has focused on the ways in which ozone pollution may interrupt plant-insect interactions during pollination. This review aims to explain and categorize current knowledge about the various ways in which increased levels of ozone in the atmosphere may impact the process of pollination. I focused on studies which investigated the effects of ozone exposure on flowering plants or insects during pollination. It is clear that exposure to ozone in insect pollinators can lead to changes in mobility [2], behavior [1,2], and perception of volatile organic compounds, which plants release for signaling and communication [8]. There is also evidence that when plants are exposed to ozone, their reproductive performance [4], visual features [3], and signaling compounds are affected [9,10]. However, it is unclear if ozone pollution will have a significant enough impact on pollination to negatively impact agricultural yields and the survival of wild plants.
Ozone Exposure to Plants:
Effects on Plant Visual Traits
There are a variety of effects of ozone on the visual features of plants that may impact pollination, including anatomical and chemical changes [3]. One recent study exposed
an endangered species of alpine geranium called Erodium paularense to ozone. The scientists measured the petal area and the spectral reflectance, which is the ratio of the amount of light reflected off of a surface to the amount of light that hit the surface [3]. Using the spectral reflectance, an anthocyanin reflectance index was calculated, which estimates the content of anthocyanins (blue, purple and red pigments) in each petal. Changes in anthocyanin content would change the perceived color of the flower to pollinators [3]. The study found no significant difference in petal area after ozone fumigation, but ozone exposure did increase petal reflectance. Plants that were exposed to ambient levels of O3 had a significantly higher anthocyanin reflectance index than other treatments. The differing reflectances mean that some insects, such as flies, would see the O3-treated plants as more blue than before, though the effect was not large enough for there to be any difference in the perceived color for butterflies and bees, based on models [3]. This study demonstrates that ozone has a measurable effect on the visual attraction of flowers, which has implications for pollination efficiency in agriculture as well as for endangered wild plants like Erodium paularense.
Effects on Volatile Organic Compounds
Ozone has a strong potential to react with and disrupt VOCs, which plants release for signaling and communication [8]. Plants use various VOCs in order to attract insect pollinators, so any reactions these compounds may undergo in the atmosphere could affect the ability of insects to locate and pollinate plants [8]. A study tested how different concentrations of ozone affect the floral scent of black mustard plants, Brassica nigra, and how the scent changes affect bumblebee behavior [9]. Flowers were placed into a system of tubes in which the floral compounds were exposed to three different concentrations of O3. The floral emissions were then collected at four different distances from the flower. Bees were given the choice between two tubes that visually mimicked mustard inflorescences, each containing either clean air or the VOCs of varying O3 exposure and collection distance [9]. The study found that the ozone concentration negatively affected the concentration of VOCs in the glass tube. In the behavioral experiments, bees showed a preference for ozone-exposed floral scents at shorter distances rather than longer distances. The results indicate that ozone concentration, ozone exposure, and distance from the scent source all affected bumblebee behavior [9]. Another study conducted research on the degradation of VOCs in which rapeseed (Brassica napus) flowers were exposed to ozone. Measurements of VOCs were taken at several timepoints after O3 fumigation [10]. The study found that ozone exposure led to a decrease in monoterpenes and sesquiterpenes (VOCs that contain alkenes) and an increase in many oxygenated species, which are formed when VOCs react with ozone. It was concluded that because monoterpenes and sesquiterpenes are very important in plant-insect signaling, there could be a significant negative impact on this signaling during pollution episodes [10]. Together, these studies demonstrate how ozone negatively affects chemical compounds released from plants and that these changes affect the behavior of pollinators.
Figure 1. Floral compounds were exposed to varying concentrations of ozone and then collected at one of four different distances from the ozone source (ozone generator): Distance 0, 1, 2, and 3.
Figure 2. Bees were given the choice between two tubes that visually mimicked mustard inflorescences (shown in green and yellow). The tubes contained either clean air or VOCs of varying ozone exposure and collection distance.
Effects on Plant Reproduction
The impacts of O3 exposure on the visual and chemical traits of plants may lead to differences in plant reproductive performance. One study investigates whether plant age at the time of exposure impacts reproduction [4]. After wild mustard plants (Sinapis arvensis) were exposed to heightened ozone concentrations at various stages of life, plant reproduction was quantified by measuring the number of seeds produced, seed weight, number of total fruits, and number of visitations by pollinator insects. The study found that the plants were affected differently by O3 depending on the age at which they were exposed. Younger plants (3 and 4 weeks old) tended to have increased reproductive performance (more fruits, more seeds, and higher seed weight than control). In contrast, plants that were exposed later in life had reduced reproductive performance, though this effect was only significant in the total seed weight in plants exposed at 5 weeks old. Overall, the study concluded that younger plants respond to ozone treatment by initiating higher investment in flower production and reproduction, whereas older plants are not as flexible and have decreased reproductive capabilities due to stress response [4]. Understanding how pollution episodes at different life stages could change crop yield is of great interest to agriculture, and may impact crop management strategies in the future.
Ozone Exposure to Insects:
Effects on Insect Motility and Behavior
Research has demonstrated that insects that have been exposed to ozone show negative health effects and changes in behavior, which may impact their ability to successfully pollinate host plants [1,2]. In one recent study, fig wasps were exposed to various O3 concentrations in fumigation chambers and their behavior was recorded at different time intervals afterward [2]. There was a significant deviation in motility behavior after exposure to O3. Specifically, there was a significant decrease in activity from control in wasps exposed to high levels of ozone (120 and 200 ppb) [2]. In a similar study, fig wasps were exposed to differing concentrations of O3 and given a choice between two stems of a Y-tube: one with a fresh air control and one with a mixture of VOCs that mimicked those of the wasps’ host plant [1]. Fig wasps that had been exposed to lower concentrations (80 ppb) of ozone significantly preferred the VOCs, those that had been exposed to an intermediate concentration (120 ppb) showed no preference, and the wasps that had been exposed to the highest concentration (200 ppb) of ozone had a significant preference for the clean air over the VOCs [1]. These results suggest that the higher levels of ozone impaired the wasps’ ability to distinguish VOCs from clean air, or made the VOCs no longer attractive to the insects. Decreased mobility and ability to locate host plants could dramatically reduce the effectiveness of pollinators.
Effects on Insect Perception of VOCs
There is potential for biochemical changes to occur within insects that could alter their sensing abilities. One study exposed fig wasps and bumblebees to varying O3 concentrations and lengths of time in fumigation chambers [1]. After exposure, electroantennograms (EAGs), a method of measuring the electrical response of an antenna to a scent [1], were measured in order to evaluate the insects’ sensitivity to different VOCs. There was a clear negative relationship between O3 exposure and the ability of pollinators to respond to and detect volatile organic compounds. However, many results were not significant and the responses depended on factors including species, the specific VOC, ozone concentration, and exposure time [1]. Further effects of ozone on insect perception of plant compounds were examined in a study which used western honeybees, a species that is important to agriculture worldwide [11]. The honeybee antennae were mounted into an airflow system in which they were stimulated with different sequences of control paraffin, O3, and three VOCs [8]. Responses were measured using EAG recording devices. One of the three compounds, (Z)-3-hexenyl acetate, showed a significant decrease in antennal responses in the O3 treatment group compared to the control group [8]. These results show that ozone can cause significant effects on antennal response to some VOCs. Therefore it may be worthwhile to test the effects of various ozone concentrations on other VOCs beyond those that were tested in this study. Impaired responses to plant compounds could potentially be detrimental to pollination, which could have far-reaching impacts for wild plant populations as well as for agriculture.
Conclusion:
Understanding how and to what extent ozone impacts plant-insect pollination interactions are active areas of research. Further experimentation will help to solidify understanding of the severity of the threat of ozone to agricultural systems and wild plants. Future directions of research include the difference between short-term high-concentration ozone pollution episodes versus long-term exposure to ambient ozone levels. The mechanisms of action of ozone interference with plant and insect biochemistry are also largely unknown [12]. Despite remaining questions, it is clear that there are many ways in which pollination is negatively affected by ozone exposure. Some of these effects are nearly imperceptible even at unrealistically high experimental concentrations of ozone [4,8], meaning that they may not be relevant to real-world scenarios. For example, one study used concentrations of 1000ppb, despite current ozone concentrations not usually exceeding 100ppb [4]. Nevertheless, ozone is a threat to both agriculture and to the biodiversity of wild plants [3].
In addition to further research, there are ways in which current knowledge can already be applied. Data from studies such as the ones included in this review can inform air pollution standards [3]. Reducing NOx emissions, which are primarily anthropogenic in source (about half come from fossil fuel combustion, and a further 20% from other combustion done by humans) would be beneficial in reducing or at least maintaining ozone levels [13].
References:
- Vanderplanck M, Lapeyre B, Brondani M, Opsommer M, Dufay M, Hossaert-McKey M, Proffit M. 2021. Ozone Pollution Alters Olfaction and Behavior of Pollinators. Antioxidants [Internet]. 10(5):636. doi: 10.3390/antiox10050636
- Vanderplanck M, Lapeyre B, Lucas S, Proffit M. 2021. Ozone Induces Distress Behaviors in Fig Wasps with a Reduced Chance of Recovery. Insects [Internet]. 12(11):995. doi: 10.3390/insects12110995
- Prieto-Benítez S, Ruiz-Checa R, Bermejo-Bermejo V, Gonzalez-Fernandez I. 2021. The Effects of Ozone on Visual Attraction Traits of Erodium paularense (Geraniaceae) Flowers: Modelled Perception by Insect Pollinators. Plants [Internet]. 10(12):2750. doi: 10.3390/plants10122750
- Duque L, Poelman EH, Steffan-Dewenter I. 2021. Plant age at the time of ozone exposure affects flowering patterns, biotic interactions and reproduction of wild mustard. Sci Rep-UK [Internet]. 11(1). Article number: 23448 (2021)
- Uysal N, Schapira RM. 2003. Effects of ozone on lung function and lung diseases. Curr Opin Pulm Med [Internet]. 9(2):144–150. doi: 10.4046/trd.2020.0154
- Aizen MA, Aguiar S, Biesmeijer JC, Garibaldi LA, Inouye DW, Jung C, Martins DJ, Medel R, Morales CL, Ngo H. 2019. Global agricultural productivity is threatened by increasing pollinator dependence without a parallel increase in crop diversification. Glob Change Biol [Internet]. 25(10):3516–3527. doi: https://doi.org/10.1111/gcb.14736
- Davison, A. W., & Barnes, J. D. (1998). Effects of Ozone on Wild Plants. New Phytol [Internet], 139(1), 135–151. doi: https://doi.org/10.1046/j.1469-8137.1998.00177.x
- Dötterl S, Vater M, Rupp T, Held A. 2016. Ozone Differentially Affects Perception of Plant Volatiles in Western Honey Bees. J Chem Ecol [Internet]. 42(6):486–489. doi: 10.1007/s10886-016-0717-8
- Farré-Armengol G, Peñuelas J, Li T, Yli-Pirilä P, Filella I, Llusia J, Blande JD. 2015. Ozone degrades floral scent and reduces pollinator attraction to flowers. New Phytol [Internet]. 209(1):152–160. doi: https://doi.org/10.1111/nph.13620
- Acton WJF, Jud W, Ghirardo A, Wohlfahrt G, Hewitt CN, Taylor JE, Hansel A. 2018. The effect of ozone fumigation on the biogenic volatile organic compounds (BVOCs) emitted from Brassica napus above- and below-ground. Plos One [Internet]. 13(12):e0208825. doi: https://doi.org/10.1371/journal.pone.0208825
- Toni CH, Djossa BA, Yedomonhan H, Zannou ET, Mensah GA. 2018. Western honey bee management for crop pollination. African Crop Science Journal [Internet]. 26(1):1. doi: 10.4314/acsj.v26i1.1
- Pinto DM, Blande JD, Souza SR, Nerg A-M, Holopainen JK. 2010. Plant Volatile Organic Compounds (VOCs) in Ozone (O3) Polluted Atmospheres: The Ecological Effects. J Chem Ecol [Internet]. 36(1):22–34. doi: 10.1007/s10886-009-9732-3
- Olivier JGJ, Bouwman AF, Van der Hoek KW, Berdowski JJM. 1998. Global air emission inventories for anthropogenic sources of NOx, NH3 and N2O in 1990. Environ Pollut [Internet]. 102(1):135–148. doi: https://doi.org/10.1016/S0269-7491(98)80026-2
A Review of Recent Research into Remote Control of Stem Cell Differentiation through Light
By Jacob Pawlak, Biochemistry and Molecular Biology ’23
Author’s Note: I wrote this piece to bring attention to the exciting new field of research being conducted primarily in China that aims to control the differentiation of stem cells by irradiating them with different wavelengths of light. This non-invasive method is potentially of great value to those working in regenerative medicine and has a strong foundation of research for future exploration. I hope to introduce this fascinating concept to future researchers to pique their interest in the field.
Introduction
Regenerative medicine is the use of human bodily mechanisms to restore functionality, cure diseases, and heal injuries. In particular, this field’s research is primarily concerned with healing previously untreatable injuries to the nervous system and regrowing musculoskeletal tissue from the aftereffects of traumatic injury or disease. The body is incapable of repairing traumatic injury to the brain or spinal cord completely, and regenerative medicine aims to use stem cells as a source of new tissue. This primarily consists of manipulating stem cells into specific cell types at the injury sites. These injuries are not particularly uncommon; in just the US, an average of 17,000 people a year are hospitalized for spinal cord damage [1].
Within the field of regenerative medicine, remote control of stem cell differentiation is one of its most promising areas of research, as it avoids the major issue of complications arising from invasive procedures, such as a risk for infection or an autoimmune response. Non-invasiveness is typically achieved through the use of near-infrared light, which is capable of penetrating tissue layers to reach target sites without harming normal cells in its path [2]. Invasive procedures require large surgical teams and expose the patient to potential infection. Instead, non-invasive procedures can be done as part of outpatient care, not requiring lengthy hospital visits. Photobiomodulation has recently emerged as one of the most promising candidates for remote control of stem cell differentiation. Photobiomodulation is the act of exposing cells to specific wavelengths of light to influence gene expression and shift cellular processes towards a specific target, such as increased differentiation into a target cell type or increased proliferation of the stem cells [2]. This often takes the form of the exposed light influencing crucial biochemical pathways in the cells, “pushing” the cells towards the researcher’s target cell type or towards increased replication. Upon reaching the site, the photons can influence the cell’s genetic expression on its own, or be converted into other influential wavelengths by novel optical devices we will go on to describe in this review [2].
There are two primary cell types targeted by researchers in regenerative medicine. The first are neural stem cells, which are directed to differentiate into astrocytes, cells that act to regulate blood flow and repair the nervous system following infections and injuries [3]. The second target for control are mesenchymal stem cells, which are found throughout the body and are capable of differentiating into a wide variety of musculoskeletal cell types such as bone, muscle, and cartilage [4]. These two cell types form the backbone of photobiomodulation research due to their potential use in regenerating complex, irreparably damaged organs such as the spinal cord.
This review presents the findings of recent research into the remote control of human stem cell differentiation. While these researchers have not worked with in vivo cells, they have laid the groundwork for a wide range of potential exploration routes for further research into stem cell differentiation control via photobiomodulation and novel optical methods.
Types of Stem Cells Researched
The two primary types of stem cells being researched for remote control are mesenchymal stem cells and neural stem cells. Mesenchymal stem cells are typically selected to create bone cell cultures, while neural stem cells are directed towards forming glial cells, which support the nervous system by forming sheaths around neural pathways and regulating blood flow [3,4].
Mesenchymal stem cells have been the primary focus of novel research, due to the relative ease of acquiring human-adipose derived stem cells (hADSC). These cells are extracted from human fat tissue and are capable of differentiation into multiple cell types. Most papers have focused on increasing the proliferation of these cells alongside increasing their differentiation into osteoblasts [7-9]. These cells are primarily useful in regenerative medicine for application to traumatic injuries to the musculoskeletal system.
In both types of cells, the light triggers photoreceptor complexes that are sensitive to the upper and lower bound of visible light wavelengths, or red and blue light [5-9]. These complexes induce the cellular modifications that lead to the changes in the stem cell’s rates of proliferation and differentiation. Thus, research focuses primarily on only red, blue, and occasionally green light, as stem cells are not uniquely reactive to more moderate colors on the visible light spectrum due to lack of sufficient sensitivity.
Novel Non-Invasive Methods – Photobiomodulation
Typically in photobiomodulation research, LED diodes are placed over cell cultures to irradiate them at specific light wavelengths for approximately 60 minutes daily over the course of 5-10 days [5-8]. Once this period is complete, researchers examine the cell cultures for signs that the cells have differentiated, such as the release of signature proteins into the culture medium or through visual inspection with a microscope [5-8].
In 2019 Wang et al. was successful in multiplying the proliferation of neural stem cells by 4.3x, and their differentiation rate into astrocytes by 2.7x through treatment with low-power blue light irradiation [5]. Proliferation measures the rate of population increase of cells, while differentiation measures how many of the stem cells develop into specialized cells. A newer study in 2021 by Yoon et al. found an increase in astrocyte proliferation through red-light treatment [6]. Notably, Yoon was able to find that red light could influence astrocyte proliferation without affecting other cells in the area, demonstrating the light’s effects in an environment closer to the human body, unlike Wang’s work on isolated astrocyte cultures. These papers making use of different wavelengths of light for different situations speaks to the versatility of photobiomodulation as a method of controlling astrocyte populations.
Comparing Light Wavelengths
While some innovative work has been done with novel optical devices, most research deals with the cheaper and simpler direct application of visible light. Visible light has been applied to both neural and mesenchymal stem cells to observe their reactions and to find wavelengths that can control differentiation and proliferation of these cells.
The application of visible light can be broadly split into two categories: red and blue. Exclusively red-light wavelengths have been found to increase the proliferation of both mesenchymal and neural stem cells [6, 8-9]. Meanwhile, blue light has mixed effects. On neural stem cells, it increases proliferation and differentiation into astrocytes, whereas on mesenchymal stem cells it has been found to lower proliferation while raising the rate of differentiation into osteoblasts [5, 7-8]. Some preliminary work has been done on green light, which has been found to cause the same effects as blue light on mesenchymal stem cells, due to the two colors’ close proximity on the visible light spectrum [7].
The most promising results come from the work of Crous et al., whose team found that they could increase both differentiation and proliferation in mesenchymal stem cells by alternating red and green light irradiation, synthesizing the effects of the two wavelengths [9]. In combination with Wang Y et al.’s work on mesenchymal stem cells with single wavelength application, this suggests that the inhibitory effects of green light on proliferation are less potent than the enhancing effects of red light, and may even be overwritten completely. This alternation between lower energy red light and higher energy green light poses the clearest path forward for future research into direct light application to stem cells, as increasing both effects is synergistic for tissue regeneration and injury repair.
Novel Non-Invasive Methods – Upconversion Nanoparticles (UCNPs)
While most research is conducted exclusively with the application of light, novel optical devices have been developed to work in conjunction with light application for finer control of stem cell differentiation. Upconversion nanoparticles (UCNPs) are artificial, nano-scaled lattices of various metal ions that exhibit the capacity to upconvert photons, a process that involves absorbing two lower-energy photons and releasing them as a single higher-energy photon [1, 13]. These are especially useful in regenerative medicine research as they are easily taken in by cells [13]. Wang K. et al and Zhang Y. et al. both used UCNPs in conjunction with near-infrared (NIR) light to control stem cell differentiation [11-12]. Both teams irradiated their cell cultures with NIR light, which can penetrate deeper than higher-energy light. This NIR light then activated UCNPs within the cultures to release UV light that activated stem cell differentiation factors from where they were loaded onto the UCNPs. Wang’s team was able to increase mesenchymal stem cell osteogenic differentiation, while Zhang’s team successfully observed increased differentiation into glial cells, a broad category which includes astrocytes and other nervous system support cells.
Additionally, UCNPs are not exclusively used to release differentiation factors, as Wang M et al.’s team was able to use UCNPs to upconvert NIR light into visible blue light to achieve deeply penetrating visible light exposure, which has high potential for use at injury sites [5]. The use of UCNPs can circumvent the problems of direct application of UV light to cell cultures, such as genetic damage and low tissue penetration. These UCNPs could provide a tool by which stem cells can be influenced in more selective regions, as their area of effect is limited to tissue sites where they have been directly implanted.
However, while UCNPs have utility, they still pose a challenge to future regenerative medicine research in that they must be somehow applied directly to the target stem cells, requiring an invasive method such as injections. This is a common issue that different research teams have run into. A novel alternative to UCNPs has been developed by Zhang S. et al that applies NIR light to copper sulfide nanostructures [10]. These nanostructures produce electromagnetic oscillations upon stimulation with NIR light that have been found to increase the differentiation of hADSCs into neuron-like cells. While innovative, this method still requires the invasive placement of copper-sulfide nanomaterials at the site of target stem cells to impact their differentiation. Although it provides a potential alternative to UCNPs, this method has not been tested by any other research teams on stem cell cultures and requires a great deal of further research before it can be implemented as a regenerative medicine procedure. Regardless of the nanobiology tools selected, researchers still must identify a way to place their developed structures near target cells.
Future Possibilities
A potential future for photobiomodulation research lies in the combination of Wang M et al.’s work with UCNPs in combination with visible light application and the alternating light method of Crous et al. to achieve increased proliferation and differentiation with relatively non-invasive deep tissue injury site access [5, 9].
Additionally, Crous’ work with earlier neural photobiomodulation studies gives researchers a way to potentially further increase astrocyte proliferation and differentiation by combining Wang M. et al.’s blue light method with Yoon SR et al.’s red light method, thereby activating two different gene expression pathways simultaneously [5-6].
The alternating light method requires further inquiry, but Crous et al. have delivered promising results in the form of increased cell movement towards a specific direction in their alternating light research [9]. This directionality is important for regenerative medicine, as cells need to be directed to grow and differentiate at specific points in injury sites to prevent undesired cell growth that could interfere with normal tissue function. Directional application of green and red light could be used in specific patterns to direct mesenchymal stem cells to grow towards a target site. Specific control over the shape and structure of stem cell differentiation is the next step for regenerative medicine research, as it allows for the construction of more complicated tissues and structures for larger injuries and for potential use in organ regeneration.
Ultimately, this research is based on the application of light; the specifics of potential applications can still be tweaked. As previously mentioned, LED diodes are placed to irradiate samples for roughly an hour a day for approximately a week [5-8]. Scientists have prioritized similar methods to achieve comparable results with each other, but the use of such regular conditions leaves photobiomodulation open for a great deal of further experimentation, as optimized application of visible light has not yet been determined. Longer or shorter exposure times, alongside lowering or raising the power of the light sources has not yet been attempted on stem cell cultures. Furthermore, work with direct light has not been performed on cells that are heavily obscured from the light source, as would be expected at the site of a deeply placed traumatic injury in a clinical setting.
Once photobiomodulation has been optimized and readied for clinical use, it is likely that further work will be performed on not just cell cultures, but on in vivo stem cells and 3D structures of stem cells. In vivo refers to cells experimented on in live organisms, rather than in isolated cultures. In vivo stem cells come with the problem of difficult to control environmental conditions, but they more accurately simulate tissue conditions. Given additional advancements in bioprinting technology, stem cells in 3D structures like hydrogels have the potential for applications of light at different angles. However, a wide array of new environmental variables would require many years of preparatory work to make up for a lack of current research. Theoretically, it may be possible for a 3D printed structure of stem cells in hydrogels to be selectively irradiated with light to grow more complex tissue formations. As such, photobiomodulation has several avenues for future research to explore as biotechnology advances.
Conclusion
The remote control of stem cells has seen great advancements in the past five years, with research on novel optical devices, a variety of wavelengths, cutting-edge manipulation methods, and the production of two different categories of human stem cells. The field has even more potential in the future, especially through the combination of different research team’s work, through synthesizing the use of different wavelengths of light, UCNPs, and currently unrealized advances in biotechnology and nanotechnology. The concept of applying light to cells to control them is an appealing one, and the field will likely expand as methods become more standardized and easier to implement in molecular biology labs. The past five years of research have laid a solid foundation for future research into remote control of stem cell differentiation, and future advances may grant regenerative medicine immensely useful tools for treating traumatic injuries to the nervous system and musculoskeletal system.
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Smoking Cigarettes as a Potential Mechanism in Developing Alzheimer’s Disease
By Barry Nguyen, Biochemistry and Molecular Biology ‘23 & Vincent Tran Neurobiology, Physiology, and Behavior ‘23
Authors Note: During my study abroad in South Korea, I was taken back by the number of people smoking cigarettes in the streets. As a country that valued health and beauty, I was surprised by the frequent sights of civilians smoking cigarettes. I then realized that not many people are aware of the cognitive effects cigarettes may induce. We both wrote this review in hopes of spreading awareness of the link that many are not cognizant of.
Introduction
Alzheimer’s Disease (AD) is an irreversible neurodegenerative disease that is characterized by neuronal loss, memory impairment, and cognitive dysfunction (Wallin et al. 2017). It is the main form of dementia in the aging population and it has been projected to quadruple in the coming century. AD pathogenesis is caused by a variety of factors–smoking cigarettes being a very common environmental factor in today’s society. Cigarettes contain thousands of organic compounds that have the capacity to induce adverse health effects (Wallin 2017). Epidemiological studies strongly show cigarette smoking as an important risk factor in AD (Yuen-Shan Ho et al. 2012). Smoking cigarettes not only doubles the risk for developing cognitive disorders, but it also accelerates the rate of cognitive decline. Approximately 2 billion people worldwide use tobacco products, mostly in the form of cigarettes (Durazzo et al. 2014) and given the current projection of AD, it is becoming increasingly paramount to further investigate the relationship between smoking cigarettes and cognitive decline. In this review, we delineate 3 strongly supported mechanisms of tobacco use that manifest and contribute to AD pathogenesis, as well as discuss the societal factors that underlie individual differences in severity of AD symptoms.
Smoking-Associated Neurological Pathologies
Increased Cerebral Oxidative Stress
Maintaining the biochemical integrity of the brain is essential for its normal functioning. Oxidative stress (OxS), in addition to its capacity to onset various vascular pathologies (Chavez et. al, 2007), may also impair cerebral biochemistry (Salim 2017). Oxidative stress (OxS) is a phenomenon that is caused by free radicals, or chemical entities with an unpaired electron. Free radicals are common by-products of metabolic processes, and among which are reactive oxygen species (ROS) that have undergone a one electron reduction (Chavez et. al, 2007). When an excess amount of (ROS), reactive nitrogen species (RNS), and other oxidizing agents are produced (Durazzo et. al 2014), and the antioxidant system is unable to keep up with such radical formation, oxidative stress occurs (Salim 2017). In general, the resulting physiological pathologies include modification of biomolecules, which results in defective cellular signaling and accumulation of malfunctioned proteins. With this cascade of negative events induced by OxS, the imbalance between production and detoxification of ROS can have serious consequences on many of our physiological systems, and in particular, the brain.
Cigarettes are composed of approximately 5,000 combustion products and contain high concentrations of free radical species (Durazzo et. al 2017). Smoking inhibits the synthesis of antioxidant species, thereby propagating free radical formation and the consequences of oxidative stress. The human brain, in particular, is vulnerable to OxS damage due to its high metabolism and relatively low antioxidant enzymes. With this said, smoking cigarettes may have profound consequences on the brain.
To detect oxidative stress in the brain and its differential manifestations among smokers and nonsmokers, scientists divided a group of 9 male rats into two groups: four in the control and five in the cigarette smoking group (Ho et. al 2012). The rats in one group were exposed to sham air, or “clean air” to serve as the control while the rats in the experimental group were exposed to cigarette smoke for one hour a day for 56 days. After 56 days, the rats were euthanized and brain tissue was retrieved.
Figure 1. Anti-8-OHG antibody was used to visualize the levels of oxidative stress present in the hippocampus (Ho et. al 2012).
To detect levels of oxidative stress, researchers used anti-8-OHG, an antibody that stains biomarkers of oxidative stress and looked at regions in the brain responsible for memory. 8-hydroxy-2 deoxyguanosine (8 OHDG) and 8-hydroxyguanosine (8-OHG) are OxS biomarkers generated when guanine, a nucleotide present in DNA and RNA, is oxidized by reactive free radicals. In the IHC stainings, a higher fluorescence was observed among the experimental group as compared to the control, suggesting smoking cigarettes as a potential inducer in cerebral oxidative stress. Rats exposed to smoking show a significant immunoreactivity of 8-OHG in the dentate gyrus, which is a region in the brain responsible for memory (Fig. 1a and b), and CA3 (Fig. 1C and D) as compared to rats in the control group. The immunoreactivity of 8-OHG in the experimental group suggests that smoking does indeed induce oxidative stress by oxidizing the guanine nucleotide present in the DNA.
Decreased Expression of Synaptic Proteins
Synapsins are synaptic proteins that are essential for the normal functioning of the brain (Yuen-Shan Ho 2012). Synapsins belong to a family of phosphoproteins and are important for synapse development, neurotransmitter regulation, and nerve terminal formation (Mirza 2018). Current Alzheimer’s literature reveals a substantial involvement of malfunctioned synapsins in the development of AD. Namely, synaptic loss in the neocortex and limbic system, both regions important for higher order functions such as emotional responses, cognition, and spatial reasoning, may be responsible for the cognitive alterations in Alzheimer’s patients. Additionally, disturbances in synapsin homeostasis have revealed cognitive deficits and defective neurotransmitter transmission in Alzheimer’s patients (Lin et. al 2014).
In the same experiment investigating cigarettes’ capacity to induce neurological dysfunction, scientists observed a decreased expression of Synapsin 1, one of three isoforms of the protein (Ho et al. 2012). Using immunohistochemistry, the smoking group showed a reduction of fluorescent intensity, inferring decreased expression of Synapsin 1. These results further bolster the capacity of tobacco use in its contribution to AD pathogenesis due to the significance reduction in the Synapsin 1 protein as observed in the results. Furthermore, cigarettes’ ability to induce small scale pathological changes in the brain suggests its domino-like effect on cognitive function.
Figure 2. Immunohistochemical staining reveals significant reduction in Synapsin 1 protein between the control and smoking group (Ho et al. 2012).
Abnormal Phosphorylation of Tau Proteins
Tau pathology, a hallmark of Alzheimer Disease pathology, manifests due to the abnormal phosphorylation of Tau protein (Neddens 2018). This hyperphosphorylation of Tau results in Tau aggregation and are collectively known as neurofibrillary tangles (NFT), a histopathological marker for AD (Miao 2019). Oxidative stress in particular has a capacity to promote Tau pathology due to its fatty acid product which provides a direct link to mechanisms that induce NFT formation (Liu 2015). The mechanism in which OxS plays in the phosphorylation of Tau and subsequent aggregation is dependent on the type of oxidant and the specific amino acid sequences involved (Federica et. al 2019). For example, oxidation of cysteine residues have been observed to be involved in Tau aggregation, suggesting the phenomenon to be a disulfide bond mediated process.
Evidence linking oxidative stress and Tau hyperphosphorylation can be supported in an experiment utilizing Buthionine Sulfoximine treatment, which induces oxidative stress in M17 neuroblastoma cells (cancers of nerve cells) by inhibiting the synthesis of glutathione, a chemical important in the maintenance of the ROS equilibrium. Researchers were able to link HO-1, an oxidative stress biomarker, with an increase in hyperphosphorylation of PHF-1 sites. PHF sites, or paired helical filaments, are the structural constituents of neurofibrillary tangles, a pathological hallmark of AD. Taken together, smoking related OxS may serve as a fundamental mechanism in the pathogenesis of AD and indirectly influence AD pathogenesis by propagating the formation of NFT (Durazzo et. al 2014).
Possible Determinants of AD Differential Manifestations
As devastating as Alzheimer’s disease can be, the extent of its harm varies across a wide spectrum, and some people face greater damage or faster onset than others. Such variations in Alzheimer’s effects might be linked to not just biological but also environmental factors. As such, societal differences in the population can underpin the impact that various effects have on patients’ lifestyle and functioning with Alzheimer’s. This idea that Alzheimer’s effects are dependent on an individual basis is centered around an individual’s reserve against Alzheimer’s and other forms of dementia. Reserve against the effects of brain damage refers to the potential to alleviate dementia symptoms and progression and is further categorized into brain reserve and cognitive reserve.
Brain Reserve and Educational Attainment’s Connection to AD
Brain reserve describes how a larger amount of brain mass could offset the amount of damage that it would take for brain function to start being impaired. As patients afflicted by neurodegenerative diseases like Alzheimer’s could potentially lose more neurons and synapses before onset of clinical symptoms, those with larger brains could have better mitigation against symptoms of dementia (Bartrés-Faz et. al, 2011). With smoking linked to Alzheimer’s development, smokers could likely be diminishing the brain mass that would be buffering the rate at which neurological decay leads to impairment of memory and everyday functions.
Variations in individuals’ brain reserve could be associated with and predicted by individuals’ lifetime educational attainment. As such, a study using structural MRI analysis compared regional cortical thickness among a sample of individuals with different educational attainment. Those with more years of education were found to have larger regional cortical thickness, which was used to compare differences in brain size (Liu et al., 2012). This positive correlation between education level and cortical thickness demonstrates the positive impact of further education on development of more brain reserve.
Cognitive Reserve and Educational Attainment’s Connection to AD
Cognitive reserve is the concept that differences in learned cognitive processes can help the brain compensate for damage or dysfunction by relying on different functional approaches. As cognition for each individual relies on different recruitment patterns of neurons and synapses, individuals with more extensive neural networks would be more likely to compensate for the loss of neurons in a network vital for specific cognitive tasks (Bartrés-Faz et. al, 2011). Therefore, the same amount of brain damage to two individuals with similar brain sizes and physiologies could potentially result in differing effects in their functioning, due to differences in cognitive reserve.
Furthermore, differences in cognitive reserves can be attributed to lifetime educational or occupational levels, with epidemiological studies showing that individuals with less than 8 years of education have a significantly higher chance of dementia (Stern, 2012).
Access to educational opportunities has been unequally distributed across socioeconomic lines, with higher education’s high costs making it significantly more accessible to the middle and upper classes. Furthermore, there has also been a disparity in the racial distribution of Alzheimer’s in the U.S., with African Americans having the highest prevalence of AD followed by Hispanic Americans.
With smoking already presented as a risk factor for Alzheimer’s, its risk is compounded by the lessened reserve that is associated with education. Demographic studies demonstrated an inverse association between chances of smoking and educational attainment, with those who have less years of education being more prone to starting (Maralani, 2013). With those who smoke likely to have less education, such individuals would increase physiological risks of acquiring AD while also being more susceptible to developing AD at an earlier time.
Conclusion
Although smoking has been known to be the root perpetrator in a multitude of health risks and diseases, its effect on neurological health warrants increased scientific and public attention. As Alzheimer’s remains without a definite cure, current treatments revolve around managing symptoms and prevention of risk factors. With how smoking involves increased cerebral oxidative stress, decreased expression of synaptic proteins, and abnormal phosphorylation of Tau proteins, recent findings reiterate the necessity of avoiding smoking cigarettes to minimize further risks of developing AD. In the case that Alzheimer’s does develop in individuals, they can have a higher quality of life living with symptoms depending on their educational history, reiterating society’s need for better access to education.
Smoking cigarettes can produce 3 substantive effects that may contribute to the pathogenesis of AD: affecting synaptic proteins, increasing oxidative stress, and raising levels of hyperphosphorylated Tau protein.
References:
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Reviewing Methods of Studying Epigenetic Drift in Monozygotic Twins
By Pranjal Verma, Neurobiology, Physiology, and Behavior ‘25
Introduction
Twin births made up 3.11% of American live births in the year 2020 [1]. There are two types of twin pairs: monozygotic (MZ), or those consisting of identical genomes, and dizygotic (DZ), or those consisting of genomes with 50% similarity (the same as siblings) [2]. The identical nucleotide sequences of MZ twins can be used to monitor chemical changes to gene expression due to environmental factors over time, the study of which is known as epigenetics [3-5].
Such environmental effects on the genome result in a phenomenon known as epigenetic drift, in which the epigenome changes over time. Specifically in MZ twins, older twin pairs tend to display more epigenetic differences than their comparatively younger twin pairs [6, 7]. This may be why twins start to differ in physical characteristics as they age. Currently, the most common epigenetic changes that have been observed are the methylations of cytosines at cytosine-guanine base pairs, as well as the acetylation of histones [3]. In this review, we will consider both modifications separately and will discuss studies investigating both types of genetic modifications.
Acetylation and Methylation of the Genome on a Molecular Level
Figure 1. Variations in the methods of histone modification. Above pictured are methylated histones and condensed DNA, which are noncoding. Below, pictured are acetylated histones and decondensed DNA which are ready to code for gene expression.
Mechanism of Histone Acetylation
Histone acetylation is one of the most commonly observed methods by which genes are activated in the epigenome. Acetylation changes the structure of the chromatin in the genome, typically by the effects of transcription activators known as histone acetyltransferases (HATs) and histone de-activators known as histone deacetylases (HDACs) [8, 9]. Interactions between HATs and HDACs determine the nature of the epigenome. For example, environmental stimuli may trigger cellular signaling pathways that activate factors which recruit HATs [10, 11]. Additionally, proteins binding to methylated DNA possess a transcription-regulatory domain, which recruit HDACs to the site [12]. Thus, an increase in methylation due to the environment could increase the amount of HDACs present.
Mechanism of DNA Methylation
Another common method of epigenetic change is through cytosine methylation in CpG sites, or a guanine nucleotide following a cytosine nucleotide in the 5’3’ direction [13]. This methylation is primarily caused by the transfer of a methyl group onto the C5 position of cytosine by DNA methyl transferases (DNMTs), and can be used as an epigenetic clock to determine chronological age [14]. DNA methylation also may have different effects in various regions of the genome—for example, DNA methylation can regulate tissue-specific gene expression, but is also important in X chromosome inactivation [15].
Studies Conducted on Epigenetic Drift
Longitudinal Studies
Few longitudinal studies have been conducted to measure epigenetic drift by assessing changes in DNA methylation. Longitudinal studies, in which the same subjects are followed throughout different stages of their lives, allow for an increased understanding of changes in gene expression over time, as the data is received from the same person [16]. Martino et al. conducted one of these studies, measuring the DNA methylation of CpG sites of buccal epithelial cells, or constantly shed squamous epithelial cells lining the inside of the cheek, of MZ and DZ twins from ages birth to 18 months. The study found that while the DNA methylation of some twins became more dissimilar over time, some twins were actually more similar as they aged. This phenomenon of becoming more similar over time is known as epigenetic convergence, and is thought to be an effect of the tendency of a population to regress to the mean, a phenomenon in which a group displays characteristics closer to the average as opposed to more extreme values [17]. Similarly, it was also found that of the twins who displayed epigenetic convergence, most had higher rates of dissimilarity at birth and were thus moving toward the average DNA methylation. Nevertheless, high rates of all epigenetic change were found after birth in this study, and it was concluded that such changes arose from stochastic and environmental factors, including the maternal environment from which they were born and their exposure to famine [18-20].
Wong et al. conducted a similar study with human twins from ages 5 to 10 years, and found that inter-pair correlation in the DNA methylation of the dopamine receptor 4 gene (DRD4) was similar in both MZ and DZ twins. This finding suggests that these correlations in the DRD4 gene are influenced by factors that impact these twins who live in the same environment, and indicates that DRD4 methylation may not be heritable. They also found significant low correlations between the DNA methylation of the serotonin transporter gene (SLC6A4/SERT) of MZ and DZ twins, indicating that the methylation of SERT is attributable to the unique environmental experiences of each child, and is not heritable. These findings show that the environment has a visible impact on the methylation of the genome, and that this impact begins taking place early in life [21].
Cross-sectional Studies
Cross-sectional studies have supported the existence of epigenetic drift, and have indicated that accordingly epigenetic differences increase with age [19]. Cross-sectional studies describe studies in which different subjects are studied at varying life stages. These studies are useful for understanding the relationship between exposures or diseases to the epigenome, but cannot be used to track genetic changes in the same subject over time, given that these studies use point measurements with different individuals [16]. Fraga et al. studied 80 Caucasian twins from Spain, and measured the acetylation of global histone H3 and H4 and DNA methylation via total 5-Methylcytosine content. In the case of acetylation in the MZ twin pairs, the youngest pairs were the most epigenetically similar, while the older pairs were much more distinct from one another. This implies that the MZ pairs grew to be more epigenetically distinct over their lifetimes, and supports the existence of epigenetic drift. Similar to what they discovered in regards to acetylation marks, Fraga et al. also found that twin pairs with the most different methylation sequences were either older, had spent more time apart, or had experienced different natural health difficulties. In other words, younger MZ twin pairs were more epigenetically similar in regards to their methylation patterns. These findings indicate strongly that there is a direct correlation between increasing age and the number of epigenetic differences among MZ twin pairs [22].
Conclusion
Epigenetic drift is the phenomenon in which the genome changes over time due to stochastic environmental factors, and is the reason that the genomes of older MZ twins are more different than those of younger MZ twins [3, 4]. MZ twin studies, both longitudinal and cross-sectional, allow for the examination of both time-related and exposure-related changes in the genome, and ultimately help create a better understanding of the dynamic nature of the epigenome.
The cause of such epigenetic change is also yet to be determined, as changes in gene expression continue well after reproductive age, meaning that these epigenetic changes cannot be passed down to the next generation. Interestingly, the changes induced by the environment may also be nonadaptive, further confusing the purpose of epigenetic drift [3]. Further longitudinal studies must be conducted in order to determine these effects, and to ultimately help understand the purpose of epigenetic drift.
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Safety and Efficacy of CAR-T cell therapy for Refractory or Relapsed B-cell Acute Lymphoblastic Leukemia
By Palak Arora
Author’s Note: I wrote this review article because it was an assignment for me, for the course UWP102B. We were instructed to choose any topic from the field of biology which presented me with a wide range of possibilities. I was not sure where to begin my search but one day while I was scrolling through social media, I heard about CAR T-cell therapy as a potential cure for cancer and I was very intrigued. The scientific community has been searching for this for a very long time and this new treatment is a huge breakthrough. This article will provide some background and explore research that has been done for CAR T-cell therapy. I want to bring awareness to my readers about this topic and also inspire young scientists to pursue research in this field since there are still many questions that have been left unanswered.
Abstract
The purpose of this review is to present the readers with an overview of the advancements in CAR T-cell therapy and areas in which more research is needed. CAR T-cell therapy is a modern approach in treating acute lymphoblastic leukemia. The modified T cells target a specific antigen on malignancies and help eliminate them. CD19 and CD22 are the antigens that are currently under investigation by researchers and the goal is to increase remission rates with the least amount of adverse events during recovery and prevent relapse as much as possible. Bispecific targeting of antigens and the subsequent use of allogeneic hematopoietic stem cell transplantation post-treatment are being examined as potential solutions to these challenges however further research is required to confirm these hypotheses and discover new approaches.
Introduction
Acute Lymphoblastic Leukemia (ALL) is the most common type of cancer in pediatric patients. This disease affects the blood and the bone marrow such that immature white blood cells are rapidly created from the bone marrow due to a genetic mutation that tells them to keep dividing. Lymphocytes are a type of white blood cells and there are two main types: B cells and T cells. ALL can affect both cell types but primarily affects B cells. In normal cases, mature B lymphocytes growing in the bone marrow function in the immune system by producing antibodies. But these leukemic cells are not as good at fighting infections, and as their numbers grow, they take up space that healthy red white blood cells could otherwise take [1]. Each B lymphocyte makes one kind of antibody that is highly specific for one unique antigen. These populations of B-cells are usually inactive, but as soon as one encounters a“non-self” or foreign antigen, the B cell is activated and begins to rapidly expand, producing multiple copies of itself. They display the antibody on their surface and as soon as they bind another antigen, they will also stimulate helper T cells which mount a defense against the “non-self” protein (an antigen). But the leukemic (cancerous) cells are not able to function properly due to an incomplete maturation process and are not as effective in fighting infections [1]. B-cell ALL is generally treated with chemotherapy or targeted immune cell therapy. After initial treatments, approximately 20% of pediatric and young adult patients relapse, suggesting chemotherapy alone is not enough to treat them [2]. Immunotherapy approaches that redirect T-cells to malignancies have been used in conjunction with chemotherapy, and have been proved to be effective in achieving complete remission (CR) [2]. These approaches include the use of tisagenlecleucel or CAR-T cell therapy, and Blinatumomab, a Bispecific T-cell engager (BiTE) which is a protein that simultaneously activates CD3 on T-cells and an antigen on the malignant cell in order to redirect T-cells towards the malignancy.
This review will focus on research from the years 2018-2022 in order to inform the readers about the current research in the field of CAR T-cell therapy to treat refractory or relapsed B-cell ALL in pediatric and adult patients. CD19 targeted CAR T- cell therapy has been successful in achieving high remission rates in pediatric patients but treating adult patients with B-cell ALL has been a significant challenge due to antigen loss post-infusion leading to a higher proportion of relapses and adverse events. Determining and preventing the risk factors for potential relapse is currently an active area of research.
Figure 1. Stem cell differentiation: This disease affects the blood and the bone marrow such that immature white blood cells are rapidly created from the bone marrow due to a genetic mutation that tells them to keep dividing. Lymphocytes are a type of white blood cells and there are two main types: B cells and T cells. ALL can affect both cell types but primarily affects B cells.
What is CAR T- Cell Therapy?
Chimeric Antigen Receptor (CAR) T-cell therapy is a form of immunotherapy in which a patient’s white blood cells are modified and an artificial receptor, CAR, is added to it, allowing for recognition of specific antigens on cancer cells [3]. Through the process of leukapheresis, white blood cells are extracted and separated. These cells are used to generally target the CD19 antigen and are utilized by the FDA-approved medication tisagenlecleucel-T. After modifications, the cells are added back to the patient’s bloodstream and progress is measured by estimating complete remission rates and through biomarkers like minimal residual disease. Minimal residual disease is a term for the small number of cancer cells left in the body post-treatment.
Tisagenlecleucel vs Blinatumomab
Blinatumomab is another FDA-approved medication that is used to treat B-cell ALL. The major difference between the two approaches taken by Tisagenlecleucel vs Blinatumomab is that CAR-T cell therapy uses the 4-1BB co-stimulatory domain which enhances CAR-T cell proliferation while Blinatumomab does not. Verneris et al. (2021) conducted an experiment to indirectly compare the two medications and observed higher CR rates with tisagenlecleucel (82%) than with blinatumomab (39%). They also observed consistent higher overall survival (OS) rates in patients treated with tisagenlecleucel than those treated with blinatumomab. This study by Verneris et al. (2021) was informed by two major studies: ELIANA and MT103-205. The researchers utilized patient data from these previous studies to determine which immunotherapy approach, Blinatumomab or Tisagenlecleucel, is more safe and effective in treating acute lymphoblastic leukemia in pediatric and young adult patients. The previous studies were single-arm, so no comparisons could be made between the two types of treatment. However, Verneris et al. (2021) controlled for patient variables and used statistical analysis to make an indirect comparison between the two. They observed higher CR rates with tisagenlecleucel (82%) than with blinatumomab (39%). They also observed consistent higher OS rates in patients treated with tisagenlecleucel than those treated with blinatumomab. A potential third variable problem that could also explain these results is that patients in the ELIANA trial were heavily pre-treated before tisagenlecleucel infusion while those in the MT103-205 trial were not. Moreover, the ELIANA trial included pediatric and young adult patients while MT103-205 only included pediatric patients. This poses a significant difference in median ages, possibly affecting the results. The sample size in this study was large enough to be generalizable and the results proved to be statistically significant with a p-value of <0.0001for CR rates and a p-value of <0.001 for OS rates. This study is of relevance to newly enrolled patients with B-cell ALL who are considering their treatment options and might benefit by being able to compare these two types of treatments even if it was an indirect comparison [2]. While this indirect comparison provides a good starting point, further double-arm studies are needed to confirm these results.
Current challenges in CAR T- cell therapy
Dosage and Side effects
For CAR T-cell therapy to be effective, a minimum number of cells (108 CAR T-cells) need to be infused. Higher number of cells increases the chances of achieving remission. But increasing the number of cells also increases the side effects experienced by patients. One of the most common side effects experienced by 80% of patients is Cytokine Release Syndrome (CRS) which is a life-threatening consequence characterized by the dysfunction of multiple organs. Other side effects include febrile neutropenia characterized by a high risk of infection (experienced by 40% subjects), unresolved hematopoietic cytopenia by day 28 (characterized by a reduction in mature blood cells), transient neuro-psychiatric events, and tumor lysis syndrome (a large amount of tumor cells simultaneously releasing their contents into the bloodstream) [4]. Balancing the dosage of CAR T-cells without knowing which patients are at a higher risk of developing these side effects remains a significant challenge and is a potential area for research.
Antigen loss
CAR T-cell therapy functions by targeting antigens on malignant cells using artificial receptors. Researchers have observed, however, that after the initial infusion, more than 60% of these patients relapse due to CD19 antigen loss [5]. Without the antigen on the leukemic B-cells, the modified T cells are not able to bind to and eliminate them. This also means that a second infusion of CAR T-cells would not be helpful since CAR T-cell persistence is not the problem. It is not yet known whether antigen loss can be prevented but researchers are still looking into biomarkers for relapse.
Predicting and preventing relapse
Minimal residual disease (MRD)
Observing minimal residual disease is the most common way to determine the safety of CAR T-cell therapy in a clinical setting. There are two ways to measure this: Next-generation sequencing (NGS) and Flow cytometry. The NGS assay sequences and tracks rearranged tumor-specific immunoglobulin sequences while flow cytometry utilizes blood and bone marrow samples to measure the physical and chemical characteristics of individual cells to estimate the number of malignant cells. MRD positivity has been hypothesized to be a predictor of relapse and in their study, Pulsipher et al. (2022) present statistically significant results to affirm the hypothesis. The researchers also compared the two methods, NGS assay, and Flow cytometry, and learned that the Next Generation Sequencing technique was much more sensitive than Flow cytometry in detecting MRD positivity. After looking at multiple potential biomarkers and demographic characteristics, the researchers found no significant effect of age, cytogenic or genetic risk, sex, or prior therapy on relapse within a year after tisagenlecleucel infusion. They did however observe that persistence of B-Cell aplasia (CAR T-cells damaging normal B-cells) and detection of NGS-MRD to be high-risk factors for relapse [6]. Current research has been focusing on methods like allogeneic hematopoietic stem cell transplantation (allo-HSCT) to reduce MRD positivity and therefore prevent early relapse. Researchers are also looking into other possible antigens that might help reduce relapse rates.
Targeted Antigens
CAR-T cell therapy is designed to target specific antigens on malignant cells. The most common target is the CD19 antigen whose expression is maintained in most B-cell malignancies. According to the researchers, CD19 CAR-T cell therapy has proven to be a usually successful treatment option with a 70-90% complete remission rate for patients with relapsed or refractory B-cell ALL and yet a large proportion of patients have relapsed within a year [5]. The study by Maude et al. (2018) found that the overall remission rate was 82% in their sample of 50 patients using CD19 CAR T-cell therapy. The researchers used polymerase chain reaction (PCR) to detect Tisagenlecleucel in the peripheral blood and found no relationship between dosage and Tisagenlecleucel expansion. In their analysis of the safety of Tisagenlecleucel, they found that at least one adverse event occurred in all patients. These adverse events included, but are not limited to, cytokine release syndrome, pyrexia, decreased appetite, febrile neutropenia, and headache. Most importantly, 19 patients died after Tisagenlecleucel infusion. The study concludes that tisagenlecleucel produces high remission rates in high-risk pediatric and young adults with relapsed or refractory B-cell ALL although there are significant risks associated with this approach [7].
Therefore an alternative antigen CD22 is also under investigation as a potential solution. Shah et al. (2020) investigated the lack of alternative immunotherapy treatment options for people with B-cell ALL who have relapsed after CD19 CAR-T cell therapy. They learned that 86.2% of the participants developed Cytokine Release Syndrome (CRS), Hemophagocytic Lymphohistiocytosis (HLH) like toxicities only developed in patients who had CRS, and peak
CAR expansion occurred 14-21 days after infusion. The researchers observed that 70.2% of the participants achieved complete remission, and 87.5% of these were found to be negative for Minimal residual disease (MRD) by Flow cytometry. And 75% of the participants experienced a relapse. They conclude that CD22 CAR-T cell therapy is a highly effective treatment option for those who have experienced relapse after CD19 CAR-T cell therapy or for those who were resistant to it [8]. Moreover, the study by Pan et al. (2019) has also shown promising results with a 70.5% complete remission rate among patients with refractory or relapsed B-cell ALL [5]. Targeting these antigens by themselves has achieved high CR rates and yet relapse continues to be an issue.
Another alternative is to target the CD19 and CD22 antigens simultaneously. In this approach, researchers can edit the patient’s T cells in a way that it has a receptor for both the CD19 and CD22 antigens. This technique is used to overcome antigen loss—If one of the antigens is lost, another is still available for T-cells to target, therefore improving response rates to therapy. After reviewing the results of their experiments Dai et al. (2020) conclude that these bispecific CD19/22 CAR-T cells might provide a good alternative for adult patients with B-cell ALL who are ineligible for other treatments as this immunotherapy option is able to prevent antigen escape without an increased risk of toxicity [9].
Figure 2. CAR T-cells are programmed to attack specific antigens like CD19 or CD22 on malignant cells.
Allogeneic hematopoietic stem cell transplantation (allo-HSCT)
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a procedure in which healthy stem cells (blood-forming cells) are transferred from a donor to a patient in order to replace the patient’s own stem cells. This procedure can be used post CAR T-cell therapy as a way to increase MRD negativity by increasing the number of healthy blood cells to improve patient recovery. In their study, Jiang et al. (2019) claim that despite the promising results of CAR-T cell therapy, patients are at a high risk of relapse due to antigen escape from tumor cells and reduced CAR-T cell persistence. They, therefore, decided to investigate whether subsequent allo-HSCT could increase minimal residual disease (MRD) negativity. This was a quantitative study that observed the number of patients with adverse effects post-treatment, the one-month remission rate (CR), overall survival (OS), event-free survival (EFS), relapse-free survival (RFS), and in vivo persistence of CAR-T cells. The researchers utilized real-time quantitative polymerase chain reaction (qPCR) to measure the level of CAR gene and flow cytometry to calculate the percentage of CAR-T cells in the peripheral blood and bone marrow post-infusion. Jiang et al. (2019) observed significant differences in the EFS and RFS rate between the two groups. However, no significant differences were observed in the overall survival rate [10].
Several studies have attempted to investigate the effects of allo-HSCT in combination with CAR-T cell therapy but so far, the results have been limited and on multiple occasions contradictory. Since this is an urgent problem that needs to be addressed, Jiang et al. (2019) designed their study in an attempt to replicate and confirm the benefits of allo-HSCT. While this study observed an improvement in EFS in their experimental group, there was a previous study that observed no such differences. Jiang et al. (2019) caution that while their study has been indicative of trends, due to the short-term follow-up and non-randomization, further studies need to be conducted on a larger scale to obtain more reliable and valid results [9].
Conclusion
In conclusion CAR T-cell therapy is an effective way to treat B-cell ALL and it has been able to achieve complete remission in up to 90% of patients in clinical trials. Achieving complete remission is relatively easier in pediatric patients but both pediatric and adult patients are still very likely to suffer from relapse within the same year due to antigen loss among other reasons. This field needs a lot of research to improve patient outcomes, achieve higher remission rates, and prevent relapse as much as possible. While researchers have been able to identify high risk factors for relapse such as B-cell aplasia and minimal residual disease positivity, it is not yet known how these can be effectively reduced. Allogeneic hematopoietic stem cell transplantation might be one potential way to prevent relapse but so far, the results are very limited, and they often contradict each other. Clinical trials with a larger sample size are needed in this area of research to provide accurate and reliable results. Overall, CAR T-cell therapy has proven to be one of the greatest advancements in cancer treatments in the past ten years but the treatment plan needs a lot more refinement before it can be used to its full potential.
References:
- National Cancer Institute. 2021 Nov. 19. Adult Acute Lymphoblastic Leukemia Treatment (PDQ®)–Patient Version. Accessed 2022 Feb 11. Available from: https://www.cancer.gov/types/leukemia/patient/adult-all-treatment-pdq
- Verneris MR, Ma Q, Zhang J, et al. 2021. Indirect comparison of tisagenlecleucel and blinatumomab in pediatric relapsed/refractory acute lymphoblastic leukemia. Blood Advances. 5(23):5387-5395. doi:10.1182/bloodadvances.2020004045
- American Cancer Society. CAR T-cell Therapy and Its Side Effects. Accessed 2022 Feb11. Available from: https://www.cancer.org/treatment/treatments-and-side-effects/treatment-types/immunothe rapy/car-t-cell1.html
- Thomas X, Paubelle E. 2018. Tisagenlecleucel-T for the treatment of acute lymphocytic leukemia. Expert Opinion on Biological Therapy. 18(11):1095-1106. doi:10.1080/14712598.2018.1533951
- Pan J, Niu Q, Deng B, et al. 2019. CD22 CAR T-cell therapy in refractory or relapsed B acute lymphoblastic leukemia. Leukemia 33(12): 2854-2866. doi:10.1038/s41375-019-0488-7
- Pulsipher MA, Han X, Maude SL, et al. 2022. Next-Generation Sequencing of Minimal Residual Disease for Predicting Relapse after Tisagenlecleucel in Children and Young Adults with Acute Lymphoblastic Leukemia. Blood Cancer Discovery 3(1):66-81. doi:10.1158/2643-3230.BCD-21-0095
- Maude SL, Laetsch TW, Buechner J, et al. et al. 2018. Tisagenlecleucel in Children and Young Adults with B-Cell Lymphoblastic Leukemia. New England Journal of Medicine 378:439-448.
- Shah NN, Highfill SL, Shalabi H, et al. 2020. CD4/CD8 T-Cell Selection Affects Chimeric Antigen Receptor (CAR) T-Cell Potency and Toxicity: Updated Results From a Phase I Anti-CD22 CAR T-Cell Trial. JCO. 38(17):1938-1950. doi:10.1200/JCO.19.03279
- Dai H, Wu Z, Jia H, et al. 2020. Bispecific CAR-T cells targeting both CD19 and CD22 for therapy of adults with relapsed or refractory B cell acute lymphoblastic leukemia. Journal of Hematology & Oncology. 13(1):30. doi:10.1186/s13045-020-00856-8
- Jiang H, Li C, Yin P, et al. 2019. Anti-CD19 chimeric antigen receptor-modified T-cell therapy bridging to allogeneic hematopoietic stem cell transplantation for relapsed/refractory B-cell acute lymphoblastic leukemia: An open-label pragmatic clinical trial. American Journal of Hematology. 94(10):1113-1122. doi:10.1002/ajh.25582
Identifying R loops with DNA/RNA ImmunoPrecipitation sequencing technology
Aditi Goyal, Genetics & Genomics, Statistics ‘22
Abstract:
Non-Beta structures are nucleic acid structures that do not follow the classic beta-helix structure described by James Watson, Francis Crick, and Rosalind Franklin [1]. R loops are a class of non-B structures and are estimated to occur across 5 percent of the human genome [1]. R loops occur when RNA strands bind to DNA, creating a DNA/RNA hybrid [1]. These structures have been implicated in several biological mechanisms, including gene regulation and DNA replication [1]. In order to further understand the purpose of R loops and their impact, one must first understand where they occur [2]. To study the location of these structures, scientists employ a technique called DRIP sequencing ([DNA/RNA ImmunoPrecipitation sequencing]) [1]. This technique utilizes the standard immunoprecipitation coupled with high throughput sequencing protocol that is commonly used in ChIP seq studies [1]. As with any sequencing technique, several modifications have been made, resulting in various types of DRIP seq protocols [1]. This literature review aims to summarize some of the more common techniques employed in R loop research [2]. This review relies on a compilation of primary research papers that document the development of these techniques [3]. It discusses the variations of each technique and identifies situations where one method may be preferred over another [4]. Further, it provides insight into the drawbacks of each method and identifies areas of improvement for these types of sequencing studies [4]. Finally, this review also highlights further areas of research inspired by the data generated from DRIP seq experiments [5].
Introduction
In all organisms, maintaining genome stability is critical for biological function. Structures that threaten the overall stability and structure of an organism’s genome, therefore, are of high importance in the scientific community, as they may provide insight into several biological mechanisms. R loops are no exceptions. R loops are DNA/RNA hybrids that are formed when an RNA strand hybridizes onto a double helix DNA molecule [1]. This hybrid structure displaces one of the two DNA strands, creating the ‘loop’ structure. This structure does not follow the classic beta-helix structure described by Watson, Crick, and Franklin, and is therefore known as a type of non-B DNA structure. Non-B DNA structures are somewhat common, occurring in approximately 13 percent of the human genome [2]. R loops occur across 5 percent of the genome. These structures disrupt DNA regulation and maintenance and are therefore a critical topic of study for understanding gene regulation [2, 5, 6].
Figure 1: 3 stranded structure describing an R loop. RNA strand, illustrated in blue, displaces the purple DNA strand, creating a loop structure. The s9.6 antibody, illustrated in green, recognizes DNA/RNA hybrids.
Understanding the genomic context of a regulatory element can provide insight into its function. Therefore, a key question when studying R loops is asking where these loops form along the genome. Several studies have aimed to characterize where R loops form along the genome [3-5]. In general, R loops are not sequence-dependent. They tend to prioritize location relative to the gene body, as opposed to a specific sequence pattern. These structures seem to occur before the first intronic region of a gene. Studies also show that these structures target promoter regions within a gene. These conclusions further support the idea that R loops interact more heavily with the structure of DNA, as opposed to the sequence. Specifically, R loop formation may depend on the accessibility of the DNA strand itself, as researchers have shown that R loops tend to form in unmethylated CpG islands (regions of the genome, primarily near promoters, that contain a large number of “CG” dinucleotide repeats) [4]. The Chedin lab at UC Davis proposes the theory that R loops prevent the methylation of transcription start sites, thereby promoting the transcription of certain genes [4]. This discovery further supports the theory that R loops are regulatory elements and play a part in gene expression regulation. Of course, given the structural instability R loops cause, they are hypothesized to have positive and negative effects on overall gene regulation and maintenance.
To understand where R loops form along a genome, we need a technology that captures this hybridization and allows us to map these regions back to a reference genome. The most used methodology for this purpose is DNA-RNA immunoprecipitation sequencing or DRIP seq for short. This review aims to provide an overview of the technology, some of the commonly used modifications used in the field and highlight the potential benefits and drawbacks of the technology. Finally, this paper proposes further areas of research; DRIP seq is a critical tool for studying R loop biology and warrants the development of analytical tools designed for processing DRIP seq specific data.
DRIP seq Protocol
Like ChIP seq protocols, DRIP seq utilizes an antibody to precipitate RNA sequences that have been cross-linked to DNA sequences. Specifically, most DRIP seq protocols rely on the S9.6 antibody, due to its high specificity and affinity for DNA/RNA hybrids [7]. As a control, genomic samples are treated with RNase H before immunoprecipitation [8]. RNase H, short for Ribonuclease H, is an enzyme active in DNA replication. RNase H recognizes DNA/RNA hybrids, which occur naturally in Okazaki fragments from RNA primers, and degrades the RNA. By treating with RNase H, we can degrade R loops present in the sample, leaving genomic DNA behind. Researchers have shown that Rnase H treatment can effectively remove R loops that disrupt DNA replication mechanisms [8].
DRIP seq is coupled with high throughput sequencing and is used in conjunction with a peak calling algorithm. Peak calling algorithms identify regions of interest in the genome. Sequence reads are aligned to a reference genome, and then processed via one of many peak calling algorithms, the most common one being MACS (Model-based Analysis of Chip Seq data). MACS analyzes the aligned data, and identifies “peaks”, or areas where there is a significant pileup of sequenced data. These peaks indicate areas of interest, and inform the researcher where their target region is. At its core, DRIP seq performs a very essential task of informing researchers where R loops occur. However, given the intricacies of this research, there are several drawbacks and assumptions involved in using DRIP seq.
bisDRIP seq
One major drawback of DRIP seq is its lack of resolution. The s9.6 antibody capture technique used in DRIP seq successfully identifies DNA/RNA hybrids. However, these regions are often too broad, as DRIP seq cannot identify which regions of DNA directly bind to RNA, and which regions of DNA are flanking regions [9]. This resolution is important for understanding how R loops impact promoter regions, which are sequence-specific entities [9, 10]. Additionally, defining the boundaries of an R loop can help us understand which elements of a gene R loops directly interact with. bisDRIP seq ([bisulfite DRIP sequencing)] was developed as a method to study where R loops localize within promoter regions [9]. Bisulfite treatment is a commonly used mutagenesis technique. This chemical treatment mutates unprotected cytosines into uracil nucleotides. In this application, researchers target the ‘open’ cytosines, which are present on the displaced DNA strand. Any cytosines on the displaced DNA strand mutate into uracils. In contrast, the cytosines present in DNA that are part of the DNA/RNA hybrid are protected from the bisulfite because they are bound. As a result, these cytosines remain unchanged. Based on the region of DNA mutated on the single strand, we can define the boundaries of the DNA/RNA hybrid. The developers of this method, a team at Cornell, discovered that R loops generally have boundaries defined by the transcription start site and the first exon-intron junction [9]. This implies that R loops are variable in length, depending on the length of the first exon.
While this technique offers high resolution, it also relies on the presence of cytosines in the region. R loops have been shown to localize in regions with high GC content [4], but in situations where this is not the case, this resolution may not be attained simply due to a lack of cytosines. Another possibility is that even in a GC-rich region, the displaced strand may be more G rich, as opposed to C. If there are no or few open cytosines on the open strand, this technique will not work. Further, chemical changes of the structure of DNA can introduce great instability and can therefore make this technique difficult to implement.
Figure 2: Bisulfite treatment will convert open cytosinecytocines to uracil, allowing us to track which regions were affected by the treatment.
s1-DRIPseq
S1-DRIPseq introduces modifications to the DRIP seq protocol that dramatically improve yield and minimize background noise. The DRIP seq protocol typically uses sonication as a method of shearing DNA fragments before immunoprecipitation. However, this method is grossly ineffective at capturing R loops, as the force of sonication disrupts most R loops present [11]. Specifically, sonication shears the DNA/RNA bond, allowing the RNA strand to be displaced and the DNA strand to re-anneal to its sister strand. S1 nuclease is an enzyme that targets single-stranded nucleic acids, aka the displaced DNA strand. By digesting this single strand, researchers can target the single strand fragments based on size. Moreover, digestion of the single strand increases the stability of the DNA/RNA hybrid, allowing for more of the regions to survive immunoprecipitation. By preserving these R loops, researchers were able to identify approximately 800 novel R loop sites in Saccharomyces cerevisiae, a common model organism for studying R loop biology [11, 12]. Due to its targeted nature, this method also greatly reduces unwanted noise, further improving the resolution of peak calling methods [11].
DRIP seq Analysis
Much like ChIP seq, the next step after DRIP sequencing and alignment is to utilize some type of peak calling program. These programs are designed to identify regions that have a statistically significant number of reads aligning to that region. This metric is referred to as the “pileup”. Significant pileup indicates that an R loop is present in this region. MACS2 [Model-based Analysis of ChIP seq] has become an industry-standard in analyzing peak data. Given that the protocol for DRIP seq closely resembles ChIP seq, the same program has been utilized to analyze DRIP seq experiments.
Once peaks have been called, they need to be annotated. There exist several types of peak annotators, designed for “universal” data. They utilize different features of the genetic data to create functional annotations. UROPA ([Universal RObust Peak Annotator)] allows users to target any type of genomic feature, along with strand specificity, and anchor positions relative to the feature [13]. Similarly, programs PAVIS and HOMER are common peak calling and annotation methods but were not specifically designed for DRIP seq data [14, 15].
To address this need for a DRIP seq specific annotation platform, a team at the University of Bologna developed DROPA ([DRIP Optimized Peak Annotator)] [16]. There are several minor differences between DROPA and the three other peak annotators listed above. The primary difference is that DROPA allows for multiple gene annotations. Recall that R loops can be very long and can span over several gene features. DROPA takes this into account and allows for longer annotations than most peak callers that use gene features as anchor points [16]. While DROPA does not provide antisense peak annotation, it does drastically reduce the number of false-positive annotations to under 7 percent [16].
Drawbacks and Discussions
DRIP seq is a critical part of studying R loops. However, the process is not perfect. There are major drawbacks to using DRIP seq in R loop identification. Firstly, the s9.6 antibody has been shown to bind to RNA/RNA hybrids, in addition to DNA/RNA hybrids [17]. Additionally, when S9.6 does identify DNA/RNA hybrids, it has been proposed that there is inherently a bias in which DNA/RNA hybrids S9.6 identifies. Research points to a potential nucleotide composition bias within the antibody [18]. Interestingly, a common pattern identified was polyA or polyU. Given that R loops are GC rich, an antibody that is biased towards AU binding indicates that this antibody may result in false positives and false negatives.
Further, the S9.6 antibody only requires six nucleotides of DNA/RNA binding to identify a “hybrid” [19]. This has positive and negative implications. Only requiring six nucleotides allows this antibody to capture the smallest of R loops, which is important for studying smaller promoter regions. However, it also means that non-R loop structures may be misidentified as R loops. This hyperaffinity, combined with the antibody’s ability to identify RNA/RNA hybrids, implies that this method may identify small interfering RNA complexes along with R loops.
Another major issue with DRIP seq is the quantitative analysis. Firstly, there is no peak caller for DRIP seq data. As of now, researchers can use MACS2, which was designed for ChIP seq data, or can build a makeshift peak caller. This lack of a standardized method causes large variance between how data is analyzed across different experiments and likely leads to varying results. Additionally, peaks identified with MACS2 may not be an accurate representation of the in-vivo conditions. While ChIP seq and DRIP seq follow very similar protocols, we cannot assume that the data looks the same.
Furthering this point, the analysis of the peaks themselves is somewhat subjective. There is no set standard for what is considered a “peak” when analyzing DRIP seq alignment data. As such, different parameterization with different peak calling methodologies can result in drastically different R loop maps. This lack of standardization is rampant in current research. To combat this problem, a team at Nanjing University has compiled a database of R-loop experiments “R-loopBase”, which features over 11 different technologies, and billions of gene annotations [20]. This database is a fundamental first step towards standardization, and yet it highlights the necessity of a standardized protocol, as it features so many variants in the field.
This issue extends beyond the analytical component to the preparation of DRIP seq samples as well. As discussed earlier, sonication is a common method of shearing double-stranded DNA during sample preparation. However, if an endonuclease is used, it can drastically alter the results. The Halasz team in Hungary investigated several variables in the DRIP seq lab protocol and concluded that using restriction enzyme digestion overrepresents longer R loops as compared to those in open reading frames [21]. They propose a standardized preparation method to help normalize physical variation between datasets [21].
Conclusion
R loops remain an elusive subject in molecular biology. They have often been characterized as the double-edged sword of gene regulation. They have been identified as critical components of transcription termination, with evidence pointing to catastrophic results if R loops are removed. And yet, they are undoubtedly a key player in genomic instability and have also been linked to Fragile X syndrome, a genetic condition that can cause intellectual disabilities and cognitive impairment [22]. There is also some evidence to suggest that R loop formation is a contributing factor in Huntington’s disease, breast, ovarian, and colon cancer, as well as Prader’s Willi Disease [23]. Tools like DRIP seq allow us to understand how these elements interact with DNA on a genome-wide scale and provide critical insight into what types of interactions are occurring. Given the inherent entropy of in vivo cell systems, standardization across DRIP seq methodologies is critical, in hopes of reducing noise and improving statistical significance in peak calling algorithms. If more reliable data can be made available, there is huge potential for applications of artificial intelligence in this field. R loop prediction would save researchers countless hours and resources, by potentially allowing them to forgo DRIP seq methodologies and rely on a predictive neural network to tell them whether an R loop is expected to be present at the loci of interest. This pattern detection program could also elucidate the mechanisms behind why R loops tend to form in certain hotspots over others. However, to make these discoveries, we must first develop tools and standards across the entire DRIP seq protocol, both in the lab and in analysis. R loop biology has boomed across the last decade and will only continue to grow. As such, this field demands that we invest the resources in developing tools specific to studying R loops and other non-B DNA structures.
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Mitochondrial Dysfunction and Alzheimer’s Disease
By Nathifa Nasim, Neurobiology, Physiology, and Behavior ‘22
Author’s note: Based on my interest in exploring Alzheimer’s pathology, I have been interested in the molecular mechanisms that drive neurodegeneration. After working on a project on mitochondrial blockers and Alzheimer’s disease at the Jin lab at the MIND Institute, I found numerous intersections between neurodegeneration and mitochondrial dysfunction, which I seek to explore in this review.
Introduction
Mitochondria are critical for energy production across the body, and are especially crucial in the brain. Not only does the brain require significantly more energy in relation to its mass compared to other organs, but it also has limited glycolytic capacity (the maximum rate of glycolytic ATP production) relying mostly on oxidative phosphorylation for meeting its high energy demands [1]. Due to this, complications with the brain’s mitochondria that affect its capacity for oxidative phosphorylation can have severe consequences on overall cognitive function. Mitochondrial dysfunction has been implicated in the pathology of various neurodegenerative diseases such as Parkinson’s disease, Huntington’s disease, Leber’s hereditary optic neuropathy, and, the focus of this review, Alzheimer’s disease (AD) [2]. Although the exact mechanisms behind the progression of AD is still unclear, recent research points towards various ways in which abnormalities in oxidative phosphorylation, or more specifically, the mitochondrial electron transport chain (ETC) – a series of protein complexes which are the sites of oxidative phosphorylation – result in various types of cellular damage which align with various hallmarks of AD pathology such as atrophy, AB aggregation, and cognitive decline.
Electron Transport Chain Deficiency
Impaired energy metabolism is one of the earliest and most well-documented signs of AD [4, 5]. As the mitochondria is primarily responsible for cellular energy production, this appears to directly implicate some aspect of mitochondrial dysfunction in the disease pathology. Supporting this, mitochondrial abnormalities in AD brains have been observed even before the emergence of neurofibrillary tangles, one of the key pathological indications of AD; this suggests that mitochondrial dysfunction is one of the earliest steps in AD pathology [4].
Research has verified that the deterioration of energy production in the AD brain was not caused by a lack of mitochondria, but rather deficiency in the electron transport chain [2]. The ETC is one of the means by which the cell produces ATP: four complexes utilize energy from electrons to create a proton gradient, and the influx of protons is coupled to ADP phosphorylation. Parker, et al studying various aspects of the mitochondrial electron transport chain, found an overall decrease in activity of all enzyme complexes involved in the ETC, especially in the cytochrome c oxidase, one of the last steps of the ETC. This was supported by previous research identifying significant decreases in cytochrome c oxidase activity [2, 7]. The brain’s continuous need for energy means that a short period without glucose or oxygen leads to cell death. Therefore, damage to the complexes of the ETC results in neuronal death and atrophy due to the lack of energy production, which is characteristic of AD [1].
ETC Damage linked to Free Radical Production
As the ETC is linked to AD characteristics, the ETC is also a source of toxic free radicals, including hydrogen peroxide, hydroxyl, and superoxide, which can lead to cellular damage which also aligns with other AD hallmarks [1]. There are other processes in the cell that also contribute to redox reactions, such as the plasma membrane oxidoreductase system, but we focus on the mitochondria, and specifically the ETC’s production of these free radicals. Oxygen is reduced as the final electron acceptor to drive oxidative phosphorylation. As cytochrome c oxidase is most directly involved with oxygen in this last step, damage to cytochrome c oxidase, as well as the rest of the complexes, can directly increase reactive oxygen species (ROS) [2, 6]. ROS are free radicals which are byproducts of energy metabolism. They are maintained by a balance between production via the ETC and clearance via antioxidants and other enzymes [6, 12]. When the ETC is damaged, the electrons which pass through the chain build up earlier in the chain, such as in complex I, where the electron can be donated to molecular oxygen and create a free radical [1]. Under typical conditions, there are cellular processes in place to neutralize the free radicals, but if there is overproduction exceeding the cell’s capability to transform them, the excess of free radicals creates oxidative stress [1].
The effects of free radicals are heightened in the brain, resulting in oxidative damage that aligns with AD hallmarks. As previously mentioned, the brain has a high demand for oxygen in addition to a high iron content, both of which enable ROS production. The brain is also especially vulnerable to ROS damage due to comparatively lower antioxidant defenses. Furthermore, the brain is the final destination of many polyunsaturated fatty acids throughout the body – such as omega-3 fatty acids – and the increased polyunsaturated fatty acids in the membranes are more sensitive to free radical damage due to lipid peroxidation, or when lipids with carbon-carbon double bonds are attacked by free radicals [1]. Synaptic mitochondria are typically more affected by oxidative stress, which leads to synaptic damage and loss, thereby affecting neurotransmission [8]. The organismal effect of this may be cognitive decline, characteristic of AD. Oxidative stress can also lead to atrophy. When EC dysfunction and oxidative stress passes a certain threshold, molecules stored within the mitochondria are released due to increased permeability of its membranes; this is part of the pathway that leads to cell death activation [6]. As mentioned, widespread atrophy or neuronal death is characteristic of AD pathology, which also results in cognitive decline. In addition to these two ways in which ROS is linked to AD, ROS damage is also involved in a positive feedback chain, exacerbating its effects. Additionally, overproduction of ROS induces conformational changes in proteins that affect ETC function causing them to “shut down” the mitochondria; the resulting dysfunction increases ROS levels, creating a cyclical spiral towards widespread atrophy [6].
mTDNA, Aging, and Alzheimer’s
Another critical effect of ROS is damage to mitochondrial DNA (mtDNA). Free radicals such as ROS can cause DNA double strand breaks, protein crosslinking, and mutations via base modifications [5]. The mitochondria is especially susceptible to DNA damage as mtDNA lacks histones. In nuclear DNA, histones are proteins that tightly wind DNA, which protects against UV damage, for instance, by reducing the exposed surface area; studies have indicated that this organization protects against free radical damage as well. mtDNA’s lack of histones due to its smaller size results in greater possibility of free radical damage [1, 5]. Moreover, the proximity of the mtDNA to the site of ROS production (in the mitochondria) also increases the likelihood of damage [5].
The mtDNA mutations are especially apparent in AD, primarily due to the mutations’ connection to the ETC. Studies have indicated increased oxidative damage of mtDNA in AD patients, notably a three-fold increase compared to healthy brains [5]. A study of AD patients also identified the specific sequences of mtDNA which most commonly suffer damage, and these were linked to the activities of the complexes of the ETC [9], and specifically, to decrease cytochrome oxidase activity [5]. As previously discussed, these damages to the ETC ultimately result in neural loss and damage which may explain the cognitive decline in AD patients [1,6]
Research suggests that ETC activity lowers with age, and one of the hypotheses behind this correlation is the accumulation of mutations with age [6]. As age is one of the risk factors for AD, the question arises whether the accumulation of mtDNA mutations and damage is simply a result of aging as AD is diagnosed later in life. A study exploring this identified higher mutation rates in mtDNA in some, but not a majority, of AD brains. They suggest that although mtDNA mutations increase with age, the mutation rate of some individuals is higher, leading to a higher probability of AD-specific mutations which increase the likelihood of dementia [9].
Mitochondrial Damage and AB
Given the involvement of mitochondrial dysfunction in AD pathology, research is being conducted to elucidate the connection between it and one of the primary characteristics of AD: amyloid plaques. Amyloid plaques are conglomerations of AB protein, which results from irregular splicing of the amyloid precursor protein (APP.) The nature of APP’s interaction with mitochondria can be explained either by overproduction of APP leading to mitochondrial dysfunction, or mitochondrial damage somehow triggering amyloid plaques.
AB has been shown to interfere with mitochondrial function through inhibiting cytochrome oxidase activity, and therefore increasing free radical activity and damage [7]. On the other hand, it has also been observed that inhibition of cytochrome oxidase promotes APP cleavage to AB, resulting in another positive feedback loop where AB inhibits the ETC and causes resulting damage, whereas the inhibition itself also promotes AB [6]. Furthermore, a study found that deficiencies in the ETC, and consequent ATP depletion, increased the possibility of APP cleavage to the AB isoform prone to aggregation, possibly due to more exposure to proteases [3, 10]. This would result in the accumulation of amyloid plaques characteristic of AD. The upregulation of mitochondrial genes in AD patients also supports a connection between the organelle and AD pathology [7], as it may be a compensatory response to the detrimental effects of APP on mitochondrial function.
One hypothesis to explain the means by which APP interferes with mitochondria is that mutant APP derivatives (the AB isoforms prone to aggregation) enter the mitochondria and disrupt the ETC, thereby generating free radicals [7]. Evidence for this chain of reasoning is that γ secretase, which is needed to cleave APP, is found inside the mitochondria. This suggests that after full length APP enter the mitochondria, they are cleaved there, upon which they may interfere with the mitochondrial proteins [7]. Another possible explanation for the damage to mitochondria was demonstrated by another study which indicated that accumulation of APP blocks mitochondrial protein transport channels, also contributing to mitochondrial dysfunction [4].
Conclusion: the Mitochondrial Cascade Hypothesis
Given the mitochondria’s crucial role in the maintenance of cellular bioenergetics, the organelle is likely a critical aspect of numerous facets of neurodegeneration, which are still under research. An emerging “mitochondrial cascade hypothesis,” seeks to highlight the importance of mitochondria in AD pathology. It ties together the various ways in which mitochondrial dysfunction is linked to the cascade of degenerative processes that occur in AD, all of which we have discussed so far. As higher ROS production rates lead to an accumulation of mitochondrial DNA damage, this decreases the ETC’s efficiency, which reduces overall oxidative phosphorylation and increases ROS production. This augmentation of ROS production triggers AB production from APP, leading to increased AB (and therefore amyloid plaques) which in turn also reduce ETC activity. Meanwhile, decreased oxidative phosphorylation and energy production in these neurons results in apoptosis, which in the large scale creates atrophy [6]. As Alzheimer’s is one of many neurodegenerative diseases with no cure, further research into the mitochondrial cascade hypothesis has the potential to expand the limited therapeutics available to treat the disease so far.
References:
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The Role of Microglia in the Two Hallmarks of Alzheimer’s Pathology
By Nathifa Nasim, Neurobiology, Physiology, and Behavior ‘22
Author’s note: While in the Jin lab at the MIND Institute, I was introduced to the intersection between inflammation and neurodegeneration, specifically in the context of Alzheimer’s disease. My interest in this relationship has primarily been in manipulating inflammatory pathways to investigate the effects on the disease. However, I wanted to step back and understand how they connected, and compile a review on microglial activation as a bridge between the two.
Introduction:
Alzheimer’s, the most common form of dementia, is a neurodegenerative disease characterized by progressive loss of memory and cognitive function. It is still largely untreatable: the last drug approved by the FDA was released nearly two decades ago. Currently, there are only a few available treatments, all of which deal with alleviating symptoms rather than affecting any of the underlying pathology [1]. There are two primary hallmarks of Alzheimer’s disease: amyloid plaques and neurofibrillary tangles (NFTs). Amyloid plaques are formed from aggregations of small amyloid beta protein (Aβ); these amyloid beta are the product of cleavage of amyloid precursor proteins found in the membrane of neurons. Neurofibrillary tangles, on the other hand, form from tau protein, which stabilize neuronal microtubules and therefore allow for transport from the cell body to other parts of the neuron. Hyperphosphorylation of tau (a signaling mechanism) leads tao its detachment from the microtubule and aggregation into neurofibrillary tangles [2, 3].
Both amyloid plaques and NFTs are implicated in neurodegeneration and cognitive loss. Amyloid plaques are thought to be precursors that trigger a cascade culminating in neurodegeneration. On the other hand, the loss of support for microtubules in NFTs leads to impaired axonal transport, resulting in synaptic loss and neuronal dysfunction in an Alzheimer’s brain [2]. This review will explore an emerging aspect of Alzheimer’s research, microglial activation, as a means of mitigating both of these pathological characteristics of the disease thereby providing a potential avenue for approaching treatment.
The Role of Microglia:
In order to approach microglial activation, it is necessary to establish neuroinflammation’s role in neurodegeneration. Neuroinflammation refers to the central nervous system’s immune response, activated in response to trauma, pathogens, or the amyloid protein aggregations of Alzheimer’s, among others [2, 4]. It is a necessary immune response, but an overactive or continuous inflammatory response can be harmful, as evident in the body’s release of anti-inflammatory mediators alongside pro-inflammatory cytokines [2, 4]. Proinflammatory cytokines (proteins that are critical for immune signaling) such as IL-1β, IL-6, IL-18 and tumor necrosis factor (TNF), have various adverse effects on neuronal function including neuronal death, synaptic loss, and synaptic “pruning” or stripping [2, 5]. Therefore, unmitigated neuroinflammation can drive neurological disease, and is implicated in the pathology of all neurodegenerative diseases [4].
The main instruments of neuroinflammation are microglia: non-neuronal phagocytic cells that are the primary proponents of the brain’s immune response. Microglia recognize potential pathogens or irritants through receptors, and in response phagocytose and/or degrade the irritant while releasing cytokines, chemokines and interferons, immune signaling proteins [2]. There are two microglial activation states which dictate the inflammatory response: the “M1” or pro-inflammatory state associated with exacerbating neurodegeneration, and the “M2” or anti-inflammatory state [2, 4]. It must be noted that this binary is simplified, and currently under research. The overactivation of the inflammatory response can be linked to the M1 state of microglia. When inflammatory mediators such as IL-1β were released by microglia, they amplify the inflammation by activating more microglia, creating a positive feedback loop of neuroinflammation characteristic of a diseased state.
Based on their role in neuroinflammation, researchers have looked to microglia as key players in Alzhiemer’s pathology. Numerous research studies have indicated that microglial activation is increased in Alzheimer’s by observing increased expression of microglial receptors in the diseased brain [3, 6]. An example of this is a study that utilized [11C](R)-PK11195, a carbon labeled ligand specific to phagocytic cells. The ligand’s specificity to microglia was increased, allowing it to serve as an indicator for microglial activation. They found a significant increase of microglial activation in Alzheimer’s patients. Furthermore, the pattern of microglial activation physically mirrored the disease’s progress in the brain in terms of atrophy, among other indicators [5]. The research is supported by previous studies as well, all of which suggested that microglial activation is an early event in neurodegeneration, as it was present in mild/early cases of Alzheimer’s [3, 5]. The immune response appeared to escalate into causing more damage as the disease progressed [3].
Amyloid Plaques:
Decades-old research has confirmed the involvement of microglia in Alzheimer’s by demonstrating that microglia cluster around amyloid plaques. There is a progressive increase of activated microglia closer to dense plaque buildup, as well as a linear increase of activated microglia as overall plaque numbers increase [7]. As previously mentioned, amyloid precursor protein splicing leads to a beta amyloid protein; a derivative of the splicing, sAPP-α, has been shown to activate microglia. As microglia are activated by irritants, this falls in line with the general defense role of microglia. The sAPP-α protein, especially an Alzheimer’s-causing isoform which is more likely to aggregate, acts as a threat and thereby activates microglia. As an assumed consequence of the microglial activation, the same study verified that the presence of sAPP-α also increased inflammatory protein expression [8].
Tau Protein Involvement:
In addition to amyloid plaques, microglia have more recently been linked to the other hallmark of AD, neurofibrillary tau tangles. Similar to amyloid plaques, a linear pattern between NFT’s and activated microglia has also been shown [7]. Further supporting this connection, experimental depletion of microglia has led to decreased tau propagation [9]. Interestingly, although inflammatory mediators observed in one study were increased in patients with tau tangles and neurodegeneration, this was not the case in patients with only amyloid plaques. This highlights the importance of tau in microglial activation, as well as the difference in microglial relations between the two [3].
The interconnection between microglia and tau is proposed to be due to microglial phagocytosis of damaged neurons containing misfolded tau. The tau is secreted in exosomes, and these “seeds” of misformed tau protein are capable of inducing other tau to misfold and aggregate [6, 9, 10]. Although the exact mechanism of microglia engulfing tau is unclear, this theory fits with the overall degenerative pathology of Alzheimer’s in that microglia “prune” already damaged neurons and then engulf them. This increased tau phagocytosis and consequent release of misfolded tau increases overall NFTs, thereby further aggravating the disease state.
Tau, Amyloid and Microglia:
Microglia may also play a role in the pattern of tau accumulation and growth in the Alzheimer’s brain. Typically, as the disease progresses, NFTs “grow” in specific patterns or stages, culminating in the neocortex, the part of the brain devoted to higher cognitive functioning. This accumulation of plaques and NFTs in the neocortex is theorized to be the cause for dementia [6]. The propagation of tau, however, is still not fully understood—research is being conducted on whether microglial activation could be a cause. The current understanding of Alzheimer’s pathology via the amyloid cascade hypothesis suggests that amyloid plaques precede other aspects of Alzheimer’s pathology and neurodegeneration, and that tau tangles occur as a result of the “cascade” [2]. However, a recent study proposed that microglia could be the key player in this cascade. Microglia are theorized to act on Aβ, thereby increasing tau propagation, although they are not directly implicated in tau spread. Studies have shown a correlation between activated microglia with the development of cognitive impairment and dementia, supporting the theory that microglia are responsible for the tau propagation patterns seen as AD progresses [6]. This bridge between tau and amyloid via microglia-driven inflammation is further elucidated by another study. Researchers propose that microglial activation, intended to clear amyloid, additionally activates kinase pathways, specifically p38MAPK, directly/indirectly increasing tau phosphorylation, leading to neurofibrillary tangles [11].
Figure 1. In the healthy neuron, tau stabilizes the neuron, but in the diseased state, the phagocytosis of misfolded tau culminates in the formation of more tau misfolding when it is released. For amyloid, specific cleavage sites result in oligomers prone to aggregation which ideally is phagocytosed by the microglia
Potential Influence on Treatment:
Based on the role of microglia in immune activation and its implication in Alzheimer’s pathology, inhibition of microglial activation could theoretically be neuroprotective against the disease, among other neurodegenerative diseases in which neuroinflammation plays a key role. Research published earlier this year expanded on this idea. Based on increased expression of a receptor in activated microglia found in Parkinson’s, a neurodegenerative disease similar to Alzheimer’s in that it is also marked by cognitive deficits, the researchers proposed utilizing the agonist NLY0. Not only did the administration of the agonist block microglial activation, it also reduced inflammatory mediators that in turn activate astrocytes, another glial cell, preventing the cycle of neuroinflammation to neurodegeneration. There were also reduced Aβ plaque numbers in an Alzheimer’s model, and perhaps as a result, improvements in cognition such as improved memory [1].
Conclusion:
Alzheimer’s disease is characterized by inflammation, through which microglia, as proponents of the brain’s immune response, are implicated in the development of the disease. The two main hallmarks of the disease — amyloid plaques and neurofibrillary tangles — are both associated with increased levels of activated microglia. However, in both cases, it is difficult to determine whether increased microglia are present as a result of neurodegeneration or whether they contribute to neurodegeneration. Nonetheless, emerging research places microglia as an important component of the amyloid cascade, by which Aβ and NFTs are connected. Neuroinflammation triggered by the need to clear amyloid plaques may lead to hyperactive kinase activity, hyperphosphorylating tau and leading to NFTs.
Given microglial involvement, further research is needed to investigate the potential of microglial inhibition in the treatment of Alzheimer’s, amongst other neurological diseases. However, the established interplay between microglia and Alzheimer’s pathology provides an important avenue in which to investigate related treatment options while illuminating the connection between inflammation and neurodegeneration.
References:
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