Bowdoin Science Journal

Science

Identification of Underlying Apoptotic Pathways in MCF-7 Breast Cancer Cells via CRISPRa Upregulation of HtrA2/Omi

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This experiment investigated a possible candidate for cancer treatment utilizing a cell’s own function for programmed cell death. The purpose of this study was to determine if upregulation of the apoptotic gene HtrA2/Omi in breast cancer cells would lead to increased apoptosis in the cells. Previous literature had described upregulation of apoptotic pathways as a possible viable mechanism for cancer treatment. However, this study did not find significant results to support these claims. 

Breast cancer, one of the most prevalent forms of cancer in the world, disproportionately affects women in the United States. On average, 13 percent of women in the United States will be diagnosed with breast cancer at some point during their lifetime (Breast Cancer Facts and Statistics 2023). Every year, 42,000 women die from breast cancer in the United States, with 240,000 more diagnosed with breast cancer (Basic Information About Breast Cancer 2023). 

Cells undergo a highly regulated process of programmed cell death called apoptosis that allows for natural development and growth of the organism. Through apoptosis, organisms are able to destroy surplus, infected, and damaged cells. Cancerous tumors develop when the apoptosis function of a cell is not working properly, resulting in a malignant cell that can grow and divide uncontrollably into a tumor. As apoptosis pathways can be induced non-surgically, it is a highly effective method used to control or terminate malignant cancer cells. By utilizing the cell’s own mechanism for death, research for cancer treatment has identified apoptosis as a way to target malignant tumors (Pfeffer et al., 2018). 

Research has shown that apoptosis is induced by overexpressing certain genes. HtrA2/Omi is a gene that induces apoptosis when overexpressed in the cell. When released from the mitochondria, HtrA2 inhibits the function of an apoptosis inhibitor, effectively inducing cell death (Suzuki et al., 2001). These data suggest that modulating and upregulating HtrA2 expression shows promising findings in enhancing apoptosis in breast cancer. 

CRISPR-Cas9 is a type of cellular biotechnology which can be used to study the manipulation of genomes by either adding, deleting, or altering genetic material in specific locations. This tool can be used to overexpress the HtrA2 gene in order to induce cell death. The process of CRISPR-Cas9 involves using sgRNA (a single guide RNA) with an enzyme to act as a gene-editing tool and introduce mutations into a desired target sequence in the genome. In order to modulate the HtrA2 gene, this experiment will require CRISPRa, a variant of CRISPR that uses a protein (dCas9) and transcriptional effector. The sgRNA navigates to the genome locus, guiding the dCas9. The dCas9 is unable to make a cut, so the effector instead activates the desired downstream gene expression (“Chapter 2: CRISPRa,” n.d.). This experiment will use CRISPRa technology to upregulate the HtrA2/Omi gene, which will inhibit the X chromosome-linked inhibitor of apoptosis, inducing either caspase-dependent cell death or Caspase-3 independent cell death in MCF-7 cells.

The pilot study for this experiment was conducted to determine the optimal level of Lipofectamine – which is a reagent that can be used for an efficient transfection without causing the cells to undergo apoptosis. The Lipofectamine concentration was varied to identify the fold change it would create in the expression of the target gene, HtrA2/Omi. After statistical analyses, researchers found no statistically significant correlation between the HtrA2/Omi gene expression and the Lipofectamine concentration in this experiment.

Fig. 1. After the transfection, qPCR was conducted on the control, 100% Lipofectamine, 75% Lipofectamine with sgRNA, and 75% Lipofectamine without sgRNA. The average Ct values were calculated and graphed.

Overall, the results from conducting quantitative PCR (qPCR), which shows how much of the HtrA2 was transfected, demonstrated extreme variance, indicating that there may have been errors that significantly affected these results. One possible error was that qPCR was conducted as cells were undergoing apoptosis, which would skew the results as mRNA is destroyed in cells as they die, leaving fragments behind. Another error observed throughout this experiment was high cell confluence (number of cells covering the adherent surface). Much of this experiment was conducted with cells at 100% or almost 100% confluence, which means it is possible that the concentrations of Lipofectamine that were predicted to cause efficient transfection did not work because the reagent could not enter the cells. Ultimately, it was found that a cell seeding concentration of 1*104 cells/mL worked best with regard to transformation, but the experiment still did not yield statistically significant results.

Fig. 2. For the pilot experiment, mCherry plasmid was transfected in MCF-7 cells. The following ZOE images showed the images of MCF-7 before transfection under different fluorescence as well as the merged image of both green and red fluorescence.

 

References

ATCC. (n.d.). MCF-7. ATCC. Retrieved November 17, 2021, from https://www.atcc.org/products/htb-22

Breast cancer facts and statistics, 2023. (n.d.). https://www.breastcancer.org/facts-statistics

Siegel, R. L., Miller, K. D., Fuchs, H., & Jemal, A. (2021). Cancer Statistics, 2021. CA: A Cancer Journal for Clinicians, 71(1), 7–33. https://doi.org/10.3322/caac.21654

Basic Information About Breast Cancer, 2023. https://www.cdc.gov/cancer/breast/basic_info

Pfeffer, C. M., & Singh, A. T. K. (2018). Apoptosis: A Target for Anticancer Therapy. International Journal of Molecular Sciences, 19(2), 448. https://doi.org/10.3390/ijms19020448

Suzuki Y, Imai Y, Nakayama H, Takahashi K, Takio K, Takahashi R. A serine protease, HtrA2, is released from the mitochondria and interacts with XIAP, inducing cell death. Mol Cell. 2001 Sep;8(3):613-21. doi: 10.1016/s1097-2765(01)00341-0. PMID: 11583623.

Hu, Q., Myers, M., Fang, W., Yao, M., Brummer, G., Hawj, J., Smart, C., Berkland, C., & Cheng, N. (2019). Role of ALDH1A1 and HTRA2 expression in CCL2/CCR2-mediated breast cancer cell growth and invasion. Biology open, 8(7), bio040873. https://doi.org/10.1242/bio.040873

Camarillo, Ignacio G., et al. “4 – Low and High Voltage Electrochemotherapy for Breast Cancer:

An in Vitro Model Study.” ScienceDirect, Woodhead Publishing, 1 Jan. 2014. www.sciencedirect.com/science/article/abs/pii/B9781907568152500042.

Rouhimoghadam M, Safarian S, Carroll JS, Sheibani N, Bidkhori G. Tamoxifen-Induced Apoptosis of MCF-7 Cells via GPR30/PI3K/MAPKs Interactions: Verification by ODE Modeling and RNA Sequencing. Front Physiol. 2018 Jul 11;9:907. doi: 10.3389/fphys.2018.00907. PMID: 30050469; PMCID: PMC6050429.

Mooney, L. M., Al-Sakkaf, K. A., Brown, B. L., & Dobson, P. R. (2002). Apoptotic mechanisms in T47D and MCF-7 human breast cancer cells. British journal of cancer, 87(8), 909–917. https://doi.org/10.1038/sj.bjc.6600541

Suzuki, Y., Takahashi-Niki, K., Akagi, T. et al. Mitochondrial protease Omi/HtrA2 enhances caspase activation through multiple pathways. Cell Death Differ 11, 208–216 (2004). https://doi.org/10.1038/sj.cdd.440134

Chapter 2: CRISPRa and CRISPRi. (n.d.). In A Comprehensive Guide on CRISPR Methods. https://www.synthego.com/guide/crispr-methods/crispri-

Uncovering Our Inner Overlord: How DEADbox ATPases Built Their Empire Off Regulating RNA Maturation

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Do you remember the simple days? Recall your fond memories of learning about organelles in introductory biology. This is where we learned our favorite biology fact, that the mitochondria is the powerhouse of the cell. Sigh, those were the days. Well, recently the field of biology has discovered a new type of organelles in the cell; membraneless organelles! They are formed through liquid-liquid phase separation (LLPS). If you imagine the droplets formed when you combined oil and water, that’s a form of LLPS. Membraneless organelles rely on LLPS for rapid and reversible cell compartmentalization.

In 2019, researcher Maria Hondele and her team took particular interest in investigating membraneless organelles, focusing specifically on DEAD-box ATPases (DDX) and their role in regulating them. DEAD-box ATPases keep ribonucleoprotein complexes from misfolding or building up over time. The role of DDX-mediated phase separation in compartmentalizing RNA processing is a rare cellular organization conserved across prokaryotes and eukaryotes over time (Hondele 2022). Highly conserved proteins have withstood the test of evolution and have continued to be passed down through generations without significant mutation. Hondele looked specifically at RNA-dependent DEAD-box ATPases because they regulate the RNA movement in and out of the membraneless organelles.

This investigation focused on  Dhh1, which is a DEAD-box ATPase specific to Saccharomyces cerevisiae (yeast). A wide range of assays were run to systematically determine the conditions required for the in vitro formation of Dhh1 liquid droplets. Liquid droplets are formed through LLPs and are indicators of membraneless organelles. Hondele found that liquid droplet formation is a fickle process that requires specific amounts of RNA and ATP to be added to the system and the cell environment to be at a low pH and salt concentration (Hondele 2019). Additionally from a DNA standpoint, the DDX itself must have low-complexity domain tails which means the ends of the proteins do not consist of a large variety of amino acids (Hondele 2019). 

After the initial investigation of the DDX ATPase and how it runs controls Dhh1 droplet formation, Hondele, and her team investigated DDX ATPase’s role in the regulation of RNA. Through a series of experiments, they found that DDX ATPases have played an extensive role in RNA regulation. The DDX ATPases can actually control the RNA maturation steps so they become spatially and temporally separated in distinct membraneless organelles (Hondele 2019). This means that each membraneless organelle may specialize in one step of the RNA maturation process so that the RNA must move between different organelles throughout the process. Of course, the release and transfer of RNA is regulated by ATPase activity, confirming DDX ATPase’s role as the omnipotent overlord of RNA. The DDXs derive their power from the low-complexity domains. These domains give DDXs the intrinsic ability to set up distinct compartments and when teamed up with the ATPases, they can influence the partitioning of RNA molecules between compartments (Hondele 2019).

Hondele and her team managed to uncover a complex and extensive dictatorship that has been operating for years under our very noses and in our very cells. The well-established and conserved cellular network of DEAD-box ATPases allows the RNA processing steps to be regulated, leading to DEAD-box ATPase control over maturation state, RNP composition, and ultimately RNA fate.

Unfortunately, we are still in the investigation phase and are yet to decide on how best to manipulate this dictatorship to benefit us. Current intelligence indicates that the dysregulation of DDXs could have pathological consequences that could contribute to the development of aggregation diseases, such as Parkinson’s, Alzheimer’s, Amyotrophic lateral sclerosis, and Frontotemporal Dementia (Gomes 2018). Luckily liquid-liquid phase separation has provided a mechanistic link between normal cellular function and disease phenotypes. Over time, these liquid droplets become more static and aggregated, likely leading these protein aggregates to be an end-stage phenotype after aberrant phase separation has overwhelmed cellular machinery that ordinarily reverses these altered phases (Gomes 2018). Through further study and comprehension of how DDXs contribute to these diseases, new treatments could be developed.

 

Literature Cited:

Gomes, E,. Shorter, J. The molecular language of membraneless organelles. J. Biol Chem. 2018; 294(18):7115-7127. 10.1074/jbc.TM118.001192

Hondele, M.,  Sachdev, R., Heinrich, S., Wang, J., Vallotton, P., Fontoura, B.M.A., Weis, K. DEAD-box ATPases are global regulators of phase-separated organelles. Nature. 2019; 573(7772):144-148. 10.1038/s41586-019-1502-y.

Hondele, M., Weis, K. The Role of DEAD-Box ATPases in Gene Expression and the Regulation of RNA-Protein Condensates. Annu Rev Biochem. 2022;  91:197-219. 10.1146/annurev-biochem-032620-105429. 

Sex-Specific Brain Responses: How Chronic Stress Reshapes Astrocytes Differently in Males and Females

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Chronic stress is one of the major precursors to numerous neuropsychiatric disorders, such as depression. Women are twice as likely to be affected by mood disorders and respond differently than men to current available treatments. Nonetheless, many preclinical studies are conducted only in male rodents. Investigating the sex-specific responses to stress is critical to identifying mechanisms underlying mood disorders and moving towards developing treatments suitable for sex differences (Zhang et al. 2024). 

Chronic stress is associated with increased inflammation in the brain. The astrocyte is a type of cell in the nervous system that regulates inflammation in the brain. Astrocytes are important for keeping neurons alive, maintaining homeostasis, and secreting cytokines that regulate proinflammatory factors in the brain. The morphological changes of reactive astrocytes can tell us about the inflammation in the brain. These changes include the number of branches the astrocyte has; the more branches it has, the more reactive the astrocyte is, which is a sign of increased stress and inflammation in the brain. Chronic stress can lead to hyperactivation of astrocytes, impairing their ability to control and limit the spread of inflammation. Remodeling of astrocytes through changes in their cellular branching (more cellular branching) has been observed in suicide victims and preclinical chronic stress models. A recent study at Rowan University investigated sex-specific astrocyte responses to chronic stress in brain regions associated with mood disorders. 

Figure 1. Non-reactive vs. Reactive astrocytes. Reactive astrocytes have thicker cell bodies and processes. Astrocytes become reactive in response to injury, as well as to chronic stress. Adapted from: Pekny M, Wilhelmsson U, Pekna M. 2014. The dual role of astrocyte activation and reactive gliosis. Neuroscience Letters. 565:30–38. 

The study used the unpredictable chronic mild stress (UCMS) model to model chronic stress or a lipopolysaccharide (LPS) injection to model systemic inflammation. The UCMS model in rodents induces behavioral symptoms commonly associated with clinical depression as well as physiological and neurological changes that are associated with depression, such as hypertension and learned helplessness. The protocol involves randomized, daily exposures to different stressors, such as removal or bedding, social stresses, or predator sounds/smells. This model allows for an in-depth investigation of changes associated with chronic-stress induced depression (Frisbee et al. 2015). The LPS injection leads to neuroinflammation, sickness behavior, and cognitive impairment; it is a model often used to study neuroinflammation-associated diseases in mice. LPS causes inflammation because it activates microglia, which are the immune cells in the nervous system and play a large role in neuroinflammation (Zhao et al. 2019). 

Male and female mice were randomly assigned to the control group (saline), a 4 hour LPS injection (4LPS), a 24 LPS injection (24LPS), no stress (NS), or stress (UCMS). They measured GFAP (a biological marker of astrocyte reactivity) fluorescent intensity for astrocyte expression and quantified branch points to assess astrocyte complexity in different brain regions. 

The astrocyte complexity was investigated in the hippocampus, amygdala, and hypothalamus. The hippocampus and amygdala are critical brain regions in regulating physiological and behavioral stress processes, which can be useful in the short-term but detrimental in the long-term. In the short term, they help the body respond to stressors in order to maintain homeostasis. However, these stress mechanisms can lead to long-term dysregulation of this process as they promote maladaptive damage on the body and brain under chronically stressful conditions, which compromises resiliency and health. The amygdala is involved in detecting and responding to threats in the environment; the hippocampus is important for memory. These regions work together to make emotional and salient memories strong and long-lasting. Inflammation may hinder learning and memory through structural remodeling of the hippocampus (McEwen and Gianaros 2010). The hypothalamus, which is part of the hypothalamic-pituitary-adrenal (HPA) axis, is essential for mediating the stress response, primarily through the release of stress hormones (Bao et al. 2008). 

Figure 2.  The hypothalamus, hippocampus, and amygdala. Adapted from: https://www.brainframe-kids.com/emotions/facts-brain.htm.

The study found that chronic stress-induced morphological changes in astrocytes occurred in all brain regions that were looked at, and that the effects of chronic stress were both region and sex specific. Females had greater stress or inflammation-induced astrocyte activation in the hypothalamus, hippocampus, and amygdala than males. This indicates that chronic stress induces astrocyte activation that could drive sex-specific differences, which may contribute to the sex differences of mood disorders and disease. 

To better assess astrocyte reactivity, they used the ramification index, which is the ratio between the total number of primary branches and the branch maximum. It indicates how ramified the astrocytes are, as more branches (more ramified) indicates more reactive astrocytes. The ramification index indicated that astrocytes were significantly ramified due to chronic stress or LPS injection. They also conducted analysis of morphological changes, which provides the strongest evidence of astrocyte reactivity. The following results demonstrate the sex differences due to stress in branch point and terminal point morphology measurements. 

In the chronic-stress induced inflammatory environment (UCMS), there was higher astrocyte activation in the female hippocampus and hypothalamus, as demonstrated by increased branch points (Figure 3). 

Figure 3. UCMS and LPS activate astrocytes in the hypothalamus by inducing morphological changes. A. Representative images of female astrocytes in the hypothalamus in each condition (saline, no stress, 4 hours post-LPS, 24 hours post-LPS, and UCMS). D. Branching points in the hypothalamus. There were significant differences between treatment and between sex. There were significantly more branch points for females in the UCMS condition than for males. Adapted from: Zhang AY, Elias E, Manners MT. 2024. Sex-dependent astrocyte reactivity: Unveiling chronic stress-induced morphological changes across multiple brain regions. Neurobiology of Disease. 200:106610.

In the amygdala and hippocampus in the 24LPS condition, there was increased astrocyte reactivity in females compared to males. This indicates that females are more susceptible to chronic systemic inflammation than males in these brain regions (Figure 4). 

Figure 4. UCMS and LPS activate astrocytes in the amygdala by inducing morphological changes. A. Representative images of female astrocytes in the amygdala in the saline, no stress, 4LPS, 24LPS, and UCMS groups. D. Analysis of branch points in the amygdala. There were significant differences between treatment and between sex. Females had significantly more branching points in the 24LPS condition than males. Adapted from: Zhang AY, Elias E, Manners MT. 2024. Sex-dependent astrocyte reactivity: Unveiling chronic stress-induced morphological changes across multiple brain regions. Neurobiology of Disease. 200:106610.

Astrocytes work in tandem with other cells in the nervous system, including microglia, to regulate various processes. Microglia, the cells in the nervous system important for immune response, are also important in the inflammatory response in the brain. Reactive microglia can activate astrocytes by secreting cytokines. Blocking microglia may be able to decrease the number of reactive astrocytes and apply a protective effect against inflammation in the brain. Future studies can look at the activation of microglia and how microglia and astrocytes interact in the chronic stress model. 

Overall, it is important that this study looked at sex differences since there is such a disparity among mental health disorders and treatment in women and men. Understanding the mechanisms behind the sex differences can improve the development of new medications for stress-related disorders so that both men and women can be correctly treated. 

Moreover, female susceptibility to chronic stress may mediate the increased risk for Alzheimer’s Disease. The different biochemical responses to stress, such as activity of the hypothalamic-pituitary-adrenal (HPA) axis and female-biased increases in molecules associated with AD, between females and males could be a sex-dependent risk factor for AD. Female-specific alterations in inflammation and microglial function are proposed to be one reason, but this needs more investigation (Yan et al. 2018). Understanding sex-specific disease mechanisms is essential for the development of personalized medicine, which is the use of an individual’s genetic profile to prevent, diagnose, and treat disease. Differences in mechanisms of disease between sexes will likely require different drugs for men and women to treat a variety of psychiatric and neurological disorders (Bangasser and Wicks 2017). 

 

References. 

Bangasser DA, Wicks B. 2017. Sex-specific mechanisms for responding to stress. Journal of Neuroscience Research. 95(1–2):75–82. 

Bao A-M, Meynen G, Swaab DF. 2008. The stress system in depression and neurodegeneration: Focus on the human hypothalamus. Brain Research Reviews. 57(2):531–553. 

Emotion Facts: Emotions in the Brain. [accessed 2024 Oct 29]. https://www.brainframe-kids.com/emotions/facts-brain.htm.

Frisbee JC, Brooks SD, Stanley SC, d’Audiffret AC. 2015. An Unpredictable Chronic Mild Stress Protocol for Instigating Depressive Symptoms, Behavioral Changes and Negative Health Outcomes in Rodents. J Vis Exp.(106):53109. 

McEwen BS, Gianaros PJ. 2010. Central role of the brain in stress and adaptation: Links to socioeconomic status, health, and disease. Annals of the New York Academy of Sciences. 1186:190. 

Pekny M, Wilhelmsson U, Pekna M. 2014. The dual role of astrocyte activation and reactive gliosis. Neuroscience Letters. 565:30–38. 

Tynan RJ, Naicker S, Hinwood M, Nalivaiko E, Buller KM, Pow DV, Day TA, Walker FR. 2010. Chronic stress alters the density and morphology of microglia in a subset of stress-responsive brain regions. Brain, Behavior, and Immunity. 24(7):1058–1068. 

Yan Y, Dominguez S, Fisher DW, Dong H. 2018. Sex differences in chronic stress responses and Alzheimer’s disease. Neurobiology of Stress. 8:120–126. 

Zhang AY, Elias E, Manners MT. 2024. Sex-dependent astrocyte reactivity: Unveiling chronic stress-induced morphological changes across multiple brain regions. Neurobiology of Disease. 200:106610. 

Zhao J, Bi W, Xiao S, Lan X, Cheng X, Zhang J, Lu D, Wei W, Wang Y, Li H, et al. 2019. Neuroinflammation induced by lipopolysaccharide causes cognitive impairment in mice. Sci Rep. 9(1):5790. 

Unlikely Weapon: Marburg Virus

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                  From the Tartar army catapulting bubonic plague victims to their enemies in the 14th century (Hale, n.d.) to the 2001 Anthrax attacks, bioterrorism has a long, but often understated, history. When thinking of terrorism, the general population generally focuses on the prospect of nuclear weapons. However, given the increasing issue of microbial resistance and rapid mutation of viruses, we must not ignore the potential of bioterrorism. In particular, Marburg Virus, a viral hemorrhagic fever closely related to Ebola, is one of the most promising potential biological weapons that should be further studied for prevention measures.

Background

                    Marburg Virus (MARV) was first discovered through simultaneous outbreaks of the virus in German and Yugoslavian laboratories in 1967, which is believed to have been caused by exposure to Ugandan African green monkeys. 31 people fell ill, and 7 deaths were recorded (Centers of Disease Control and Prevention, n.d.). Since the initial outbreak, there have been irregular outbreaks in Africa throughout the years, ranging from 1 to over 250 reported human cases (Centers of Disease Control and Prevention, n.d.).

                  MARV is categorized as a filovirus, which is the same virus classification as Ebola. MARV is a severe hemorrhagic fever, defined by its high mortality rate of up to 90% (Centers of Disease Control and Prevention, n.d.; Leroy et al., 2011). A MARV infection starts off with common symptoms such as a fever, nausea, headaches, and muscle pain, but quickly escalates to gastrointestinal problems (stomach pain and vomiting), respiratory problems (chest pains and coughing), neurological issues (delirium), and hemorrhagic manifestations (skin rashes, nosebleeds, and vomiting blood) (Leroy et al., 2011). Unfortunately, the severity of a MARV infection has made it a contender as a biological weapon.

Potential for Bioterrorism

                  MARV is often considered to be an effective agent of bioterrorism. According to the Centers for Disease Control and Prevention, MARV is a Category A (high-priority) pathogen based on the following criteria: a high transmission rate, high mortality rate and potential for major public health impact, potential for public panic, and requires special action for public health preparation (Centers for Disease Control and Prevention, 2024). MARV can also be aerosolized (turning infected body fluids or excrements into a fine mist) for higher transmission through the air, produced in large industrial quantities, and is spread from person to person (Filoviridae, n.d., Texas Department of State Health Services). In the Soviet Union’s Biological Weapons program, MARV was one of the strategic-operational weapons (meant for long-distance and short-distance targets) that would have been used in future wars (Tucker, 1999). The Soviet Union actually preferred MARV over Ebola because MARV’s weaponized form was more stable than Ebola’s (Filoviridae, n.d.). Considering MARV’s potential for bioterrorism, it is essential to develop prevention methods.

Vaccines in Development

                  While MARV is widely regarded as a high-priority pathogen with likely devastating consequences, there is still no known treatment or vaccine. However, within the last 5 years, two vaccine trials show great potential. One of the trials was tested on nonhuman primates, while the other trial was tested on humans. Both trials were successful in developing antibodies against MARV and didn’t have any severe side effects on the participants (O’donnell et al., 2023; Hamer et al., 2023).  These trials display promising results that can potentially mark a significant advancement in reducing the spread of MARV.

                  Initially only causing irregular outbreaks, MARV now has the potential to become a huge public health issue due to its potential for bioterrorism and high mortality rate. Therefore, the Biomedical Advanced Research and Development Authority (BARDA) of the U.S. Department of Health and Human Services awarded $21.8 million to the Sabin Vaccine Institute to continue developing a vaccine for MARV (Sabin Receives, 2022). Current vaccines in development show great potential to lessen MARV outbreak, though future studies need to continue monitoring the efficacy and safety of these vaccines. These measures highlight the importance of MARV vaccine research to protect global health from potential bioterrorism.

 

References

Centers of Disease Control and Prevention. (n.d.). About Marburg Virus Disease. Centers for Disease Control and Prevention. Retrieved July 15, 2023, from https://www.cdc.gov/vhf/marburg/about.html#:~:text=Marburg%20virus%20disease%20(MVD)%20is,within%20the%20virus%20family%20Filoviridae

Centers for Disease Control and Prevention. (n.d.). Marburg Virus Disease Outbreaks. Centers for Disease Control and Prevention. Retrieved July 15, 2023, from https://www.cdc.gov/vhf/marburg/outbreaks/chronology.html

Centers for Disease Control and Prevention. (2024, November 21). Emergency Preparedness and Response. Emergency Preparedness and Response. https://www.cdc.gov/emergency/index.html

Filoviridae. (n.d.). Federation of American Scientists. Retrieved December 7, 2024, from https://programs.fas.org/bio/factsheets/ebolamarburgfs.html

Hale, Kristina. (n.d.) Yersinia pestis as a Biological Weapon—Insects, Disease, and History | Montana State University. (n.d.). Retrieved December 7, 2024, from https://www.montana.edu/historybug/yersiniaessays/hale.html

Hamer, M. J., Houser, K. V., Hofstetter, A. R., Ortega-villa, A. M., Lee, C., Preston, A., Augustine, B., Andrews, C., Yamshchikov, G. V., Hickman, S., Schech, S., Hutter, J. N., Scott, P. T., Waterman, P. E., Amare, M. F., Kioko, V., Storme, C., Modjarrad, K., Mccauley, M. D., . . . Stanley, D. A. (2023). Safety, tolerability, and immunogenicity of the chimpanzee adenovirus type 3-vectored marburg virus (cAd3-Marburg) vaccine in healthy adults in the usa: A first-in-human, phase 1, open-label, dose-escalation trial. The Lancet, 401(10373), 294-302. https://doi.org/10.1016/s0140-6736(22)02400-x

Leroy, E.m., Gonzalez, J.-P., & Baize, S. (2011). Ebola and marburg haemorrhagic fever viruses: Major scientific advances, but a relatively minor public health threat for africa. Clinical Microbiology and Infection, 17(7), 964-976. https://doi.org/10.1111/j.1469-0691.2011.03535.x

O’donnell, K. L., Feldmann, F., Kaza, B., Clancy, C. S., Hanley, P. W., Fletcher, P., & Marzi, A. (2023). Rapid protection of nonhuman primates against marburg virus disease using a single low-dose vsv-based vaccine. EBioMedicine, 89, 104463. https://doi.org/10.1016/j.ebiom.2023.104463

Sabin Receives Additional $21.8 Million From BARDA to Advance Marburg Vaccine. (2022, September 13). Sabin Vaccine Institute. Retrieved July 21, 2023, from https://www.sabin.org/resources/sabin-receives-additional-21-8-million-from-barda-to-advance-marburg-vaccine/

Texas Department of State Health Services. (n.d.). Viral Hemorrhagic Fevers and Bioterrorism.

Tucker, J. B. (1999). Biological weapons in the former Soviet Union: An interview with Dr. Kenneth Alibek. The Nonproliferation Review, 6(3), 1–10. https://doi.org/10.1080/10736709908436760

New Development of a Skin Probiotic to Combat Eczema

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The underlying factors contributing to the common condition of atopic dermatitis, more commonly referred to as eczema,  are generally related to an imbalance in the skin microbiome. The skin is home to an abundance of different species of bacteria, and most are symbiotic with humans and provide many defenses against invading pathogens. One of these symbiotic bacteria is called Roseomonas Mucosa (R. Mucosa), and it is this bacteria that has been found to be essential to maintaining a well-balanced and healthy skin microbiome, which in turn protects us from invaders such as Staphylococcus Aureus, the primary cause of eczema. Researchers from the National Institutes of Health were recently able to find genetically different versions of R. Mucosa that were better in their protective ability and were able to incorporate them into a skin probiotic cream that is effective in safely treating eczema.

  In their study, different strains of R. Mucosa, based on their differing metabolic profiles, were applied to eczema-affected patients, and the amount of recovery was quantified and compared. (Myles, et al.,2018) These differing metabolic profiles are important because they refer to the type and amount of certain lipids (fats) that are excreted by R. Mucosa that are essential in initiating a sequence in which the epithelial (skin) layer is repaired. (Myles, et al.,2020) In addition to comparing the different strains of R. Mucosa, researchers tested the responses to different environmental conditions to see how the possible treatment would be impacted by other topically applied solutions and the general presence of certain chemicals on the skin. Part of this was done by testing the growth of different strains of R. Mucosa, as well as S. Aureus, in the presence of different commonly marketed treatment lotions with known names. (Myles, et al.,2018)

               The study found that certain strains of R. Mucosa were more effective at reducing the impacts of eczema (NIAID, 2024)(Myles, et al.,2018) and the lipids produced by the effective strains were isolated and noted. The strains that produced the helpful lipids and a sufficient quantity of them were identified (Categorized as R. Mucosa HV). (Myles, et al.,2018) When the strains of R. Mucosa and S. Aureus were placed in differing environments, it was found that while most current market treatment products don’t inhibit the beneficial R. Mucosa growth, they may aid in the harmful eczema-causing bacteria S. Aureus. This suggested that these market products not be taken in conjunction with the new probiotic treatment. (Myles, et al.,2018)

  The study and subsequent clinical trial found that the transplantation of R. Mucosa onto an affected skin microbiome that is susceptible and/or subjected to eczema can lead to a reduction of the harmful effects related to eczema. It was tested further through clinical trials and has since been rolled out under the name Defensin, produced by Skinesa. Further studies are working to form an application to the FDA in order to roll out the probiotic cream as a regulated non-prescription drug so as to be more widely available to those who may benefit from it. (NIAID, 2024)

 

 

 References

(1) Myles, I. A., Castillo, C. R., Barbian, K. D., Kanakabandi, K., Virtaneva, K., Fitzmeyer, E., Paneru, M., Otaizo-Carrasquero, F., Myers, T. G., Markowitz, T. E., Moore, I. N., Liu, X., Ferrer, M., Sakamachi, Y., Garantziotis, S., Swamydas, M., Lionakis, M. S., Anderson, E. D., Earland, N. J., & Ganesan, S. (2020). Therapeutic responses to Roseomonas mucosa in atopic dermatitis may involve lipid-mediated TNF-related epithelial repair. Science Translational Medicine, 12(560). https://doi.org/10.1126/scitranslmed.aaz8631

(2) Myles, I. A., Earland, N. J., Anderson, E. D., Moore, I. N., Kieh, M. D., Williams, K. W., Saleem, A., Fontecilla, N. M., Welch, P. A., Darnell, D. A., Barnhart, L. A., Sun, A. A., Uzel, G., & Datta, S. K. (2018). First-in-human topical microbiome transplantation with Roseomonas mucosa for atopic dermatitis. JCI Insight, 3(9). https://doi.org/10.1172/jci.insight.120608

(3) NIAID Discovery Leads to Novel Probiotic for Eczema. (2024, June 26). Nih.gov. https://www.niaid.nih.gov/news-events/niaid-discovery-leads-novel-probiotic-eczema?utm_medium=social&utm_source=linkedin&utm_campaign=news_probiotic_eczema_6262024

 

An Overview of Alzhimer’s Disease Pathogenesis

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Keywords: pathogenesis, cholinergic changes, oxidative stress, amyloid plaque, Tau protein, mutation

Introduction

As people get older, many health complications begin to arise, many of which are cognitive. One such health complication is Alzheimer’s Disease (AD), which is one of the most common cause of dementia. AD is a disease that impacts fifty-five million people worldwide and one in three people over the age of eighty five experience advanced symptoms and signs of AD (Twarowski and Herbet 2023). AD is incurable and often leads to death, and currently a lot about how this disease works and about how it can be treated is unknown. AD is a complex multifactorial disease, and scientist are looking at many different causes (Twarowski and Herbet 2023). I will be covering the current understanding of AD pathogenesis (the process by which a disease is formed) through multiple lenses and discuss current treatments for AD. 

AD Pathogenesis Overview 

Cholinergic changes: 

One of the major neurotransmitters that allows for muscle movement, regulating heartbeat and blood pressure, and certain brain functions, is acetylcholine. Acetylcholine is active in the cerebral cortex, the basal ganglia, and the forebrain, and one of the first hypotheses for AD was cholinergic changes (Twarowski and Herbet 2023). A cholinergic change refers to the changes in the cholinergic system which is a neurotransmitter (acetylcholine) system that plays a role in memory, digestion, control of heartbeat, and movement (Sam and Bordoni 2023). When the nucleus basalis degenerates, there is a loss of synaptic connections that result in the deficiency of neurotransmission  (Twarowski and Herbet 2023). This can thus impact memory and movement, which are some of the most common symptoms of AD. The initial stages of AD are related to cholinergic changes and as the disease progresses, the cholinergic system loses its function until it all function is lost, resulting in death  (Twarowski and Herbet 2023).  

Figure 1. Demonstration of the cholinergic system in a neuron (Hall 2020 Mar 13).

Amyloid plaques and Tau proteins:

Amyloid plaques and the malfunction of Tau proteins are suspected to be two of the causes of AD that both lead to disease progression. Beta amyloids are small water-soluble peptides, and plaques will form if the beta amyloids do not have a stable structure (Twarowski and Herbet 2023). This lack of structure is thought of to be a cause of mutations. These plaques exhibit toxic properties to neuronal cells which causes neurons to degenerate (Twarowski and Herbet 2023). A Tau protein is a protein that promotes the assembly of tubulin which is a protein that is involved in cell division and cell movement. A Tau protein that is not functioning due to neurotoxins will bind to other Tau proteins and create tangles inside a neuron that lead to apoptosis of the neuron (Twarowski and Herbet 2023). This accumulation of plaques can cause the Tau proteins to form together and lead to tangles, revealing how there is a link between the two cause of AD (What Happens to the Brain in Alzheimer’s Disease? 2024 Jan 19). This process usually occurs in the final stages of AD pathogenesis.  

Figure 2. Amyloid beta plaques and Tau protein tangles impact on Neuron (McLoughlin).

 

Oxidative Stress: 

Another cause of AD is increased oxidative stress, which has many implications on people with AD. Oxygen is particularly important to the brain as the brain uses around twenty percent more oxygen than other organs in the body (Twarowski and Herbet 2023). Changes related to oxidative stress, which is an imbalance of free radicals and antioxidants in the body that leads to cell damage, are often seen in people with AD. This damage is caused by lipid oxidation as a result of oxidative stress breaks bonds in DNA molecules which increases the aging and death of neurons. These changes can also influence the mutation of Tau protein into advanced glycoxidation end products (AGEs) which are toxic to neurons and also lead to the progression of AD (Twarowski and Herbet 2023).  

Figure 3. Cell undergoing oxidative stress (Moore 2022 May 17).

Mutations:

One of the main and most significant factors that is related to the pathogenesis of AD and ties all of the previous factors together is genetic mutations as mutations are related to both cholinergic changes and oxidative stress. However, mutations in the genes that encode for the amyloid precursor protein have been identified as the most dangerous genetic risk factor associated with the development of AD (Twarowski and Herbet 2023). These are mutations in the 34 allele which is the allele of apolipoprotein E have been found to occur within one and five Alzheimer’s patients, and the risk of developing AD increases threefold with this mutation. Furthermore, this mutation may lead to the amyloid beta plaques and thus cause AD (Twarowski and Herbet 2023). Mutations are thus the largest contributing cause to AD because they can have so many implications that lead to the pathogenesis of AD. 

Figure 4. DNA that has undergone a mutation (Scoville 2019).

Conclusion

AD is a disease that impacts many people and causes many deaths annually, so being able to find a cure is incredibly important. AD pathogenesis is extremely complex, and as of today, scientists do not fully understand its pathogenesis, but we are getting closer. Understanding how the processes that lead to AD pathogenesis is the first step to being able to help find treatments that will help millions of people. Thus, scientists are still working diligently to understand how this disease works and how our current understanding can be improved. 

 

 

Literature Cited

Hall A. 2020 Mar 13. ChAT in 3D: Understanding the central cholinergic system. LifeCanvas Technologies. https://lifecanvastech.com/whole-brain-imaging-of-the-central-cholinergic-system-through-immunolabeling-chat/.

McLoughlin L. A Guide To Tau Proteins & Tauopathies. Assay Genie. https://www.assaygenie.com/blog/protein-tau-and-tauopathies.

Moore M. 2022 May 17. Effects of Oxidative stress | HHC. Life Science product | Helvetica Health Care. https://www.h-h-c.com/what-is-oxidative-stress-and-how-does-it-affect-your-health/.

Sam C, Bordoni B. 2023. Physiology, Acetylcholine. PubMed. https://www.ncbi.nlm.nih.gov/books/NBK557825/.

Scoville H. 2019. 4 Types of DNA Mutations and Examples. ThoughtCo. https://www.thoughtco.com/dna-mutations-1224595.

Twarowski B, Herbet M. 2023. Inflammatory Processes in Alzheimer’s Disease—Pathomechanism, Diagnosis and Treatment: A Review. International Journal of Molecular Sciences. 24(7):6518. doi:https://doi.org/10.3390/ijms24076518.

What Happens to the Brain in Alzheimer’s Disease? 2024 Jan 19. National Institute on Aging. https://www.nia.nih.gov/health/alzheimers-causes-and-risk-factors/what-happens-brain-alzheimers-disease.

 

From Milk to Malignancy – Breast Cancer and its Metabolic Implications 

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The annual rise of cancer cases has created a high demand for new innovative treatments and has made cancer a prominent topic in the scientific community. According to the American Cancer Society (ACS), approximately 20 million new cancer cases were diagnosed worldwide in 2022, leading to 9.7 million deaths [1]. It is expected that by 2050, cancer cases will reach 35 million, largely due to population growth [1]. While significant advancements have been made in cancer research, the complexity of different cancer types presents challenges. 

One of the most prevalent forms is breast cancer, which, in 2022, was the second most common cancer in the U.S., with 2.3 million new cases, predominantly affecting women [2]. Unlike many cancers, breast cancer is not a single disease but a collection of subtypes characterized by distinct clinical, morphological, and molecular features. This heterogeneity makes it challenging to study and treat effectively. A recent study published in Nature Metabolism explores the metabolic differences between normal mammary cells and breast cancer cells [4]. Understanding these metabolic processes could pave the way for new, targeted therapies. Researchers have identified specific metabolic vulnerabilities in mammary epithelial cells, which line the breast tissue.

 

Figure 1. Non-tumorigenic Mammary Gland Components. A diagram of a non-tumorigenic mammary gland showing a cluster of alveoli containing luminal and basal cells. Luminal cells line the milk ducts and alveoli and are responsible for milk secretion during lactation. Basal cells are believed to play a role in transporting milk to the nipple during lactation. Source: Created in BioRender, [4], [10], [11].

In the normal mammary gland, various types of cells carry out specific functions, one of which is the progenitor cells. These progenitor cells generate distinct alveolar structures that continuously form in the adult breast, and their activity is crucial for maintaining normal mammary homeostasis [5]. Progenitor cells are located in the luminal compartment [6], which is also home to the luminal cells. The luminal cells play a key role in lactation by lining the milk ducts and alveoli, where they secrete milk (Figure 1)[7]. In contrast, basal cells are located around the luminal cells and are believed to function during lactation by helping to transport milk to the nipple (Figure 1)[7]. Although these mammalian epithelial cells (luminal and basal cells) are important to the function of normal mammary glands, these also serve as a tumour cell of origin [4].

In their study, Mahendralingam et al. used mass spectrometry to analyze the metabolic profiles of normal human mammary cells [8]. They discovered that luminal progenitor cells primarily rely on oxidative phosphorylation for energy, whereas basal cells depend more on glycolysis [4]. This distinction is crucial because oxidative phosphorylation is an efficient, oxygen-dependent process that generates substantial energy, while glycolysis, though faster, is less efficient and does not require oxygen — a pathway often favored by cancer cells to support rapid growth [9]. Targeting these distinct energy pathways could lead to more effective treatments for different breast cancer subtypes.

However, a new discovery was that breast cancer cells appear to adopt the metabolic programs of their cells of origin [4,9]. This complicates treatment since the cancer cells may still be vulnerable to metabolic pathways that are important for normal cell function. As a result, treatments designed to target specific metabolic pathways might not work as expected, since the cancer cells might behave similarly to the healthy cells from which they originated. 

The results from Mahendralingam et al. can form a basis for future metabolic studies that may lead to specific anti-tumoral drug therapies designed to treat specific breast cancer subtypes. This type of research lays a foundation for targeted approaches but further studies are needed to assess how findings, such as this one, can translate into clinical practice. As breast cancer continues to rise, understanding the complexity is more important than ever. 

 

Work Cited: 

  1. Global Cancer Facts & Figures. (n.d.). Retrieved October 27, 2024, from https://www.cancer.org/research/cancer-facts-statistics/global-cancer-facts-and-figures.html
  2. Global cancer burden growing, amidst mounting need for services. (n.d.). Retrieved October 27, 2024, from https://www.who.int/news/item/01-02-2024-global-cancer-burden-growing–amidst-mounting-need-for-services
  3. Sánchez López de Nava, A., & Raja, A. (2024). Physiology, Metabolism. In StatPearls. StatPearls Publishing. http://www.ncbi.nlm.nih.gov/books/NBK546690/
  4. Alfonso-Pérez, T., Baonza, G., & Martin-Belmonte, F. (2021). Breast cancer has a new metabolic Achilles’ heel. Nature Metabolism, 3(5), 590–592. https://doi.org/10.1038/s42255-021-00394-8
  5. Tharmapalan, P., Mahendralingam, M., Berman, H. K., & Khokha, R. (2019). Mammary stem cells and progenitors: Targeting the roots of breast cancer for prevention. The EMBO Journal, 38(14), e100852. https://doi.org/10.15252/embj.2018100852
  6. Tornillo, G., & Smalley, M. J. (2015). ERrrr…Where are the Progenitors? Hormone Receptors and Mammary Cell Heterogeneity. Journal of Mammary Gland Biology and Neoplasia, 20(1–2), 63–73. https://doi.org/10.1007/s10911-015-9336-1
  7. New Paradigm for Mammary Glands. (n.d.). Massachusetts General Hospital. Retrieved December 8, 2024, from https://www.massgeneral.org/cancer-center/clinician-resources/advances/new-paradigm-for-mammary-glands
  8. Mahendralingam, M. J., Kim, H., McCloskey, C. W., Aliar, K., Casey, A. E., Tharmapalan, P., Pellacani, D., Ignatchenko, V., Garcia-Valero, M., Palomero, L., Sinha, A., Cruickshank, J., Shetty, R., Vellanki, R. N., Koritzinsky, M., Stambolic, V., Alam, M., Schimmer, A. D., Berman, H. K., … Khokha, R. (2021). Mammary epithelial cells have lineage-rooted metabolic identities. Nature Metabolism, 3(5), 665–681. https://doi.org/10.1038/s42255-021-00388-6
  9. ZHENG, J. (2012). Energy metabolism of cancer: Glycolysis versus oxidative phosphorylation (Review). Oncology Letters, 4(6), 1151–1157. https://doi.org/10.3892/ol.2012.928
  10. Fig. 3 Stem cell in glandular and stratified epithelia. A A schematic… (n.d.). ResearchGate. Retrieved December 7, 2024, from https://www.researchgate.net/figure/Stem-cell-in-glandular-and-stratified-epithelia-A-A-schematic-model-depicting-the_fig3_374804603
  11. Model of normal mammary gland structure. This tissue is composed of… (n.d.). ResearchGate. Retrieved December 8, 2024, from https://www.researchgate.net/figure/Model-of-normal-mammary-gland-structure-This-tissue-is-composed-of-ducts-which-are_fig1_357239665

Genomics of severe and treatment-resistant obsessive-compulsive disorder treated with deep brain stimulation: a preliminary investigation

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Obsessive-compulsive disorder (OCD) can be severely disabling, and some patients do not respond to standard treatments like medication and therapy. Deep brain stimulation (DBS), an invasive neurosurgical intervention where thin electrodes are connected to a neuro-pacemaker and introduced into subcortical central structures of the brain to modulate pathological neuronal activity with electrical current, has shown promise for these treatment-resistant cases. However, responses to DBS vary widely, prompting a need to identify genetic factors that might predict which patients will benefit. Understanding these genetic markers may ultimately lead to more personalized, effective approaches for treatment-resistant OCD.

This study (Chen et al, 2023) conducted a preliminary genomic analysis on a small cohort of patients with severe, treatment-resistant OCD who received DBS. Researchers sequenced the patients’ DNA to examine specific genetic variants. These included instances where a single nucleotide in a genomic sequence was altered in a phenomenon known as single nucleotide variants and among other genetic markers previously associated with psychiatric disorders and traits related to treatment resistance. Statistical analysis was then applied to explore any associations between these genetic markers and the clinical outcomes of DBS in these patients.

The results identified several genetic markers such as missense variants in the gene KNCB1 that seemed to correlate with positive or negative DBS responses. However, because the study involved a small number of participants, these findings are considered preliminary. Certain genetic variants showed potential as predictors for treatment outcomes, but further research with a larger sample size is needed to validate these associations and understand the mechanisms by which they influence DBS response.

This study provides initial evidence that genetics may play a role in how patients with treatment-resistant OCD respond to DBS. If validated by larger studies, these findings could pave the way for genetically-informed approaches to selecting and optimizing DBS candidates, contributing to more precise, personalized treatment strategies for severe OCD cases.

References:

Long Long Chen, Matilda Naesström, Matthew Halvorsen, Anders Fytagoridis, David Mataix-Cols, Christian Rück, James J Crowley, Diana Pascal (2023) Genomics of severe and treatment-resistant obsessive-compulsive disorder treated with deep brain stimulation: a preliminary investigation, medRxiv , https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153313/

Infertility: The Unknown

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The term “infertility” often has a negative social stigma that is damaging to many couples hoping to start a family. The reputation that precedes infertility is often blamed on women, which can cause a lot of pressure and lead to misinformation about the topic. While infertility affects women at different stages in life, aging is an important contributing factor to the decline in women’s fertility. Infertility can be defined in many terms, but the CDC defines infertility as a woman aged 35 years or younger not being able to get pregnant after one year or longer of unprotected sex. Furthermore, a woman aged 35 years or older, can be considered infertile after 6 months of unprotected sex[1]. Many couples experience infertility correlated to genetics and reproductive health, but this problem also involves other complex issues like social, economic, and cultural implications[2]. Fertility is an important societal issue, and the World Health Organization (WHO) states that nearly 50-80 million people face some sort of infertility. Ever since the first IVF baby was born in 1978, the demand for fertility treatments has increased and driven many patients to look at the scientific world for new developments to conceive children or genetically test their embryos[3]. Science has paved a pathway with new techniques to treat infertility, like IVF, pre-implantation genetic testing or screening (PGT/S) of embryos, and other modern instruments that offer more opportunities to improve infertility care[4]. While all of these technological advancements help infertility patients, many questions remain about what the leading causes of infertility are. 

In 2009, Roupa et al. conducted a study in Greece to investigate which were the most prevalent causes of infertility in women of reproductive age[2]. In the study, the women of reproductive age ranged from 20 to over 50 years of age. This study consists of 110 infertile women who sought medical assistance from the Center for Assisted Reproduction for a period of two months. From this center, these women were randomly sampled and agreed to participate in the study. To collect data, researchers constructed a specific questionnaire that included demographic data and questions concerning their infertility.

The results from this study showcase the broad causes of infertility — specifically the top three leading causes. The first leading cause of infertility problems, 27.4%, was issues with the fallopian tubes, which may reference the blockage or scarring of the fallopian tubes[5]. This can result from malformation, endometriosis adhesions, inflammatory diseases, infections, and sexually transmitted diseases[6]. The fallopian tubes serve as channels for the transportation of eggs to the uterus[6] but if the fallopian tubes are blocked, the eggs are not able to move from the ovaries to the uterus which makes the sperm unable to fertilize the egg[5]. The second leading cause of infertility problems, 24.5%, is due to unknown causes. This is almost a quarter of the study’s results, which leads to the conclusion that further and more in-depth research needs to be done to investigate the causes of failed conception like further individualized treatment[7]. The third leading cause of infertility problems, 20.0%, was due to disorders of menstruation. Disorders of menstruation is a broad term to classify physical or emotional problems that affect the normal menstrual cycle, unusually heavy or light bleeding, and missed periods[8]. Some examples of menstrual disorders are abnormal uterine bleeding, the absence of menstruation, and Premenstrual Syndrome (PMS), to name a few[8]. Although there were other infertility causes like problems in the uterus (9.1%), sexual disorders (2.6%), and ovarian deficiency (3.6%), the three major leading causes that affected the majority of the study were fallopian tube problems, unknown causes, and disorders of menstruation.

There are disorders, syndromes, and diseases that give women insight into the possible causes of infertility they experience, but still, nearly a quarter of the study participants weren’t able to identify their issue. Although more research has started to be done, only 151 articles related to the study of infertility have been published from 2001 to 2021[9], illustrating that infertility needs to be focused on more within modern research. Age is an important factor for fertility because the health of eggs is reflected by both the quantity and quality of the eggs[10], but age is just one cause. There are more causes of infertility that women suffer from that go beyond being at a “reproductive age” that are undiscovered. The reality is that the infertility research field is understudied due to the lack of funding compared to other fields, like cancer. From 2016 to 2019, the National Institutes of Health (NIH) awarded less than 100 projects totaling around $83 million for female-based research on infertility[11], while awarding more than 16,000 grants for cancer research and over $14 billion in funding.[12]. The lack of awards, less than 100 projects awarded in three years, is a shocking statement that highlights the lack of funding the field has. Many causes of infertility are understudied because of the lack of funding, thus the rate of development has been hindered. The truth is that infertility is increasing every year, ​​and fertility rates in the United States have gradually declined from 1990 to 2019. In 1990 there were about 70.77 births each year for every 1,000 women aged 15-44, and by 2019 there were 58.21 births per 1,000 women in that age group[13]. If fertility rates continue to decrease year by year, and no stable funding is available for the sexual and reproductive healthcare system, a true epidemic will occur. The government needs to start taking this problem seriously and allocate stable funding towards researching the numerous causes of infertility. Not only would this benefit many women who have no diagnosis of infertility but it would help the fertility rates around the nation go up.

 

Works Cited –

  1. CDC. (2023, April 26). What is Infertility? Centers for Disease Control and Prevention. https://www.cdc.gov/reproductivehealth/features/what-is-infertility/index.html
  2. Roupa, Z., Polikandrioti, M., Sotiropoulou, P., Faros, E., Koulouri, A., Wozniak, G., & Gourni, M. (2009). Causes of infertility in women at reproductive age. Health Science Journal, 3, 80–87.
  3. Eskew, A. M., & Jungheim, E. S. (2017). A History of Developments to Improve in vitro Fertilization. Missouri Medicine, 114(3), 156–159.
  4. de Santiago, I., & Polanski, L. (2022). Data-Driven Medicine in the Diagnosis and Treatment of Infertility. Journal of Clinical Medicine, 11(21), 6426. https://doi.org/10.3390/jcm11216426
  5. Eunice Kennedy Shriver National Institute of Child Health and Human Development—NICHD. (n.d.). Retrieved April 18, 2024, from https://www.nichd.nih.gov/health/topics/factsheets/infertility
  6. Han, J., & Sadiq, N. M. (2024). Anatomy, Abdomen and Pelvis: Fallopian Tube. In StatPearls. StatPearls Publishing. http://www.ncbi.nlm.nih.gov/books/NBK547660/
  7. Sadeghi, M. R. (2015). Unexplained Infertility, the Controversial Matter in Management of Infertile Couples. Journal of Reproduction & Infertility, 16(1), 1–2.
  8. Igbokwe and, U. C., & John-Akinola, Y. O. (2021). KNOWLEDGE OF MENSTRUAL DISORDERS AND HEALTH SEEKING BEHAVIOUR AMONG FEMALE UNDERGRADUATE STUDENTS OF UNIVERSITY OF IBADAN, NIGERIA. Annals of Ibadan Postgraduate Medicine, 19(1), 40–48.
  9. Zhu, H., Shi, L., Wang, R., Cui, L., Wang, J., Tang, M., Qian, H., Wei, M., Wang, L., Zhou, H., & Xu, W. (2022). Global Research Trends on Infertility and Psychology From the Past Two Decades: A Bibliometric and Visualized Study. Frontiers in Endocrinology, 13, 889845. https://doi.org/10.3389/fendo.2022.889845
  10. George, K., & Kamath, M. S. (2010). Fertility and age. Journal of Human Reproductive Sciences, 3(3), 121–123. https://doi.org/10.4103/0974-1208.74152
  11. Gumerova, E., Jonge, C. J. D., & Barratt, C. L. R. (2021). Research Funding for Male Reproductive Health and Infertility in the UK and USA [2016 – 2019] (p. 2021.08.23.456936). bioRxiv. https://doi.org/10.1101/2021.08.23.456936
  12. McIntosh, S. A., Alam, F., Adams, L., Boon, I. S., Callaghan, J., Conti, I., Copson, E., Carson, V., Davidson, M., Fitzgerald, H., Gautam, A., Jones, C. M., Kargbo, S., Lakshmipathy, G., Maguire, H., McFerran, K., Mirandari, A., Moore, N., Moore, R., … Head, M. G. (2023). Global funding for cancer research between 2016 and 2020: A content analysis of public and philanthropic investments. The Lancet Oncology, 24(6), 636–645. https://doi.org/10.1016/S1470-2045(23)00182-1
  13. Bureau, U. C. (n.d.). Stable Fertility Rates 1990-2019 Mask Distinct Variations by Age. Census.Gov. Retrieved May 2, 2024, from https://www.census.gov/library/stories/2022/04/fertility-rates-declined-for-younger-women-increased-for-older-women.html



Orchid Species’ Infidelity Challenges Biological Immutability

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From researchers to botanists, the pervasive method of plant identification has relied heavily on the observation of physical characteristics. The outward appearance of an organism, or phenotype, is determined in large part by genotype, an organism’s genetic makeup (Editors, 2018). Therefore, ecological identifications often go unchallenged, and genotype is assumed based on phenotypic classification. Physical characteristics, such as color or size, are regarded as fundamental to the identity of most species, despite the subjectivity of these observations. Molecular ecologists sought to examine this reality, in conjunction with their analysis of speciation, in their 2023 study focused on East Coast orchids (Evans et al., 2023).

National Geographic defines a species as a “group of organisms that can reproduce naturally with one another and create fertile offspring” (National Geographic Society, 2023). However, this is not always what occurs in the natural world. In rare instances, two individuals of differing species may reproduce, generating progeny that are often sterile: a phenomenon defined as “hybridization”. This study, conducted by Evans et al., investigates a novel case of this cross species reproduction among the Platanthera blephariglottis, Platanthera cristata, and Platanthera ciliaris species. 

Researchers had observed that several Platanthera orchid species often grow in close proximity to each other. In these locations of overlap, plants with distinct characteristics of multiple separate species are present. This has led many to conclude, based on visual classification, that these individuals are hybrids. Historically, crosses between P. blephariglottis and P. christata have been defined as P. x canbyi, while offspring between P. blephariglottis and P. ciliaris have been defined as P. x bicolor (Figure 1). Though the crosses have been assumed based on the intermediate nature of their structures, this tells scientists little about what is happening at the molecular level. As such, they aimed to answer three questions through their work: Are these organisms truly hybrids? Which species cross? Do the genetic results match their phenotypically assigned species?

Figure 1: Orchid crosses between each species, which demonstrate intermediate characteristics between parental phenotypes.

To answer these, researchers ran tests to compare phenotypic classifications with genetic composition. They began by measuring physical characteristics (morphology), such as flower width, and averaging this data among each assigned species identity (Figure 2). DNA samples were then extracted, enabling each plant to be sequenced and sorted based on genetic composition. Overlaying the DNA samples with their paired physical measurements, researchers could see clearly the degree to which their classifications matched a plant’s genetic code. 

Figure 2: Violin plot demonstrating variation in flower morphology. These graphs visually represent the intermediate nature of hybrid phenotypes. Figure adapted from Evans et al.

After performing these tests, researchers found that each species maintained distinct morphological measurements, with the presumed hybrid offspring sorting independently between the appropriate parents. Results also demonstrated that in locations where both parents were not present, the phenotypic intermediaries disappeared. These plants are true hybrids. Yet, this is not to assert that all previous assumptions were found to be flawless. It was also revealed that researchers had genotypically misclassified several samples: many of the plants initially categorized as P. ciliaris were actually P. x bicolor hybrids, and some of the collected plants were either backcrosses (genetic products of a hybrid and pure species) or the offspring of two hybrids.

On the molecular level, they discovered that genes flowed more freely between P. blephariglottis and P. ciliaris, with P. cristata remaining more distinct. There are several potential factors influencing this semipermeable barrier to hybridization, with physical structure and typical pollinators being the most instrumental. Because both P. blephariglottis and P. ciliaris are consistently pollinated by swallowtail butterflies, their cross P. x bicolor is rather common. P. x canbyi, whose parents are only occasionally pollinated by bumblebees, is much less frequent. This distinction in pollination is due to the specialized reproductive structures tailored to each organism, which also act as a barrier to hybridization morphologically.

Hybridization maintains the potential to introduce adaptive genes or advantageous characteristics, but it also has the potential to erode the genetic makeup of a species. Posing a threat to rare or endangered individuals, crossing in this manner comes with the risk of producing an unhelpful or potentially detrimental recombination of alleles. This study demonstrated that phenotypic characteristics are not a reliable form of species identification in the field, and challenges the validity of past ecological research. If phenotype is not a reliable form of identification, how many studies might have been based on an ill informed set of genotypic presumptions? These orchids also defy the dominant definition of a distinct species, as they freely reproduce and cross, creating valid intermediates. By reproducing across species lines, these plants subvert typical notions of biological concreteness and lead us to wonder: how much do we truly know about the natural world?

 

Works Cited

Editors, B. D. (2018, March 27). Genotype vs. Phenotype. Biology Dictionary. https://biologydictionary.net/genotype-vs-phenotype/

Evans, S. A., Whigham, D. F., Hartvig, I., & McCormick, M. K. (2023). Hybridization in the Fringed Orchids: An Analysis of Species Boundaries in the Face of Gene Flow. Diversity, 15(3), Article 3. https://doi.org/10.3390/d15030384

National Geographic Society. (2023, October 19). Species. National Geographic. https://education.nationalgeographic.org/resource/species