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Treatments for Eye Strain From Screen Exposure
By Anisha Narsam, Neurobiology, Physiology and Behavior ‘23
Author’s Note: I hope to raise awareness about treatments for eye strain from screen exposure because of the current pandemic and the increase in online interactions. This article is meant for students and individuals who work on devices with screens, such as computers or tablets, and want to treat their eye strain. I chose this topic because I have noticed an increase in my eye strain since the pandemic began and I wanted to research how to alleviate this condition for myself and for my peers. Through this article, I hope readers can understand the effectiveness of a range of treatments for eye strain from screen exposure with my analysis of seven peer-reviewed journal articles.
Abstract
Excessive screen time, due to remote learning, is dramatically increasing the incidence of eye strain. Since this condition can elevate tiredness and reduce an individual’s ability to concentrate, promising treatments must be considered to avoid further ocular harm. Previous research on eye strain shows that when people spend a lot of time on their computer, they can benefit from taking frequent breaks away from their screens. However, with increased reliance on technology for everyday tasks, these techniques are not enough. As a result, treatments must be developed and implemented to counter the degenerative effects of long-term eye strain, which may eventually lead to headaches and farsightedness. This paper analyzes seven peer-reviewed journal articles centered around the effectiveness of each treatment on eye strain. Supplemental medications and ergonomic techniques show promising results for combatting dry eye and ocular pain, specific symptoms of eye strain. Studies evaluating the effectiveness of blue light glasses demonstrate conflicting results. Further research and implementation of these methods can decrease eye strain symptoms while improving concentration.
Introduction
Eye strain is one of the most common ocular conditions faced by adults and students around the world [1]. As of 2017, around 64 percent to 90 percent of computer users reported eye strain symptoms [2]. Physiologically, these symptoms result from repetitive rapid eye movements between the keyboard, screen, and other documents [2]. With more interactions taking place virtually because of the COVID-19 pandemic, addressing this condition is crucial for decreasing headaches and improving focus when completing tasks on screens. Many studies have only focused on treatment through minor modifications in a person’s behavioral tendencies, such as by following the 20/20/20 rule. This rule asks individuals to look 20 feet away from their screens for 20 seconds every 20 minutes [3]. Since taking frequent screen breaks may not be helpful for severe eye strain, the purpose of this literature review is to evaluate the effectiveness of medications [1, 4, 5], blue light-blocking glasses [6,7], and ergonomic techniques [2, 3] in combating this condition. By evaluating these treatments, we can determine reliable methods for alleviating eye fatigue.
Medication
In terms of medication, omega-3 fatty acids (O3Fas) can reduce eye strain [1]. Specifically, O3Fas treat patients with dry eye, which is a symptom of eye strain. When people stare at one location for extended periods of time, they often do not blink as much, which results in dry eye because of decreased eye lubrication [2]. On a cellular level, O3Fas has been shown to increase the density of goblet cells, which lubricate the eye. The patients chosen for the study used a computer for more than three hours each day [1]. While 120 patients received the O3Fas treatment, the remaining 236 patients received an olive oil placebo daily and their symptoms were evaluated. Each week, patients assigned a score between zero and three for symptoms such as blurry vision, dry eyes, and red eyes [1]. At the baseline, 60 percent of patients had moderate dry eye symptoms in both the O3Fas and the placebo groups [1]. By the end of the experiment, 70 percent of the O3Fas group and 15 percent of the placebo group were symptom free. In addition, Schirmer’s test was performed, which involves gently placing a filter paper onto the participants’ eyes and analyzing the cells found on this paper for tear production [1, 4]. A statistically significant improvement in dry eye symptoms was found in the O3Fas group compared to the placebo group, demonstrating the effectiveness of O3Fas in combatting dry eye resulting from computer vision syndrome [1]. They can also improve epithelial cellular morphology in the eyes while decreasing tear evaporation rates, which ends up reducing eye strain symptoms. While this study analyzed the effects of O3Fas, it did not test for how the dosage of O3Fas affects an individual’s symptoms.
Besides O3Fas, researchers examined how the dosage of a particular botanical formula can decrease eye strain, while using a machine learning-based model to predict an accurate dosage for each patient [4]. Botanical formulas are natural, plant-based ingredients and oils that are combined in order to treat or supplement a condition. This specific botanical formula is made of carotenoids, naturally derived pigments in plants that support eye health, as well as blackcurrant, chrysanthemum, zeaxanthin, and goji berry. These formulas are antioxidants and are known for their ability to absorb the blue light that typically radiates from visual display units. Researchers split the participants, who are each exposed to screens daily, into four groups. The three experimental groups ingested six, ten, or fourteen milligrams of the chewable tablet, while the fourth group received a placebo [4]. Similar to the O3Fas study, this study also asked patients to take these tablets once daily for 90 days, while self-reporting how often they felt symptoms such as eye soreness and dry eye [1, 4]. In addition, both studies used Schirmer’s test to evaluate dry eye symptoms, which found that both the 10-milligram and 14-milligram groups had increased tear production [1, 4]. Researchers input the symptoms and dosages of 56 of the participants into their machine learning model, XGBoost. The study found that the optimal dosage is 14 milligrams for 39 individuals, 10 milligrams for 17 individuals, and zero milligrams for two participants [4]. Researchers determined that the botanical formula significantly improves eye strain, while outlining the potential for machine learning to determine optimal dosages [4].
Bilberry extract (BE), another naturally-derived medication, has proven to be quite effective in reducing eye strain caused by acute video display terminal (VDT) loads, or devices with a display screen [5]. BE is loaded with anthocyanins, which are known for their ability to decrease further visual disturbance and eye strain. The participants use VDTs daily and have eye strain symptoms. Over an eight-week period, the experimental group ingested 480 milligrams of BE per day, in contrast to the placebo group [5]. The researchers evaluated their symptoms using the Critical Flicker Fusion device (CFF), which analyzes the frequency of a human eye identifying a blinking light as continuous [5, 6]. Lower CFF values correlate to less eye strain symptoms. This contrasts to the O3Fas and botanical formula studies that analyze the dryness of a patient’s eyes through Schirmer’s test [1, 4, 5]. Moreover, all three studies focused on patients with existing eye strain [1, 4, 5]. A self-reported questionnaire asked participants to rate the intensity of their symptoms on a scale from one to ten every week. Based on the CFF tests, researchers found a statistically significant lower CFF value, or less eye strain, for the BE group compared to the baseline [5].This CFF reduction was not observed in the placebo group. Participants in the BE group felt less ocular pain compared to the control group.6 The researchers argued that BE supplements can reduce eye strain caused by VDT loads, while further research can eventually analyze how BE works [5].
(a) Blackcurrant, (b) chrysanthemum, and (c) goji berry compose a botanical formula that can significantly improve eye strain [4].
Blue Light-Blocking Glasses
Medications are important treatments to consider, but there are many behavioral changes that may decrease eye strain symptoms too. One possible behavioral change is wearing blue light-blocking glasses in treating eye strain. Blue light is short-wavelength electromagnetic radiation, which ranges from around 400 to 500 nm in length, and carries one of the highest amounts of energy [7]. There have been many hypotheses previously considered, which shows how blue light could potentially cause retinal damage, especially towards the aging eye. In fact, from studies in animals, increasing amounts of blue light exposure can increase the amount of cell apoptosis in the eyes [7]. It is important to note that blue light is emitted by the sun onto Earth’s surface, but it is the excessive exposure to blue light from screens that can have negative effects [6]. Based on these previous experiments, researchers aim to understand whether or not blocking blue light is effective in preventing eye strain and retinal damage by testing the effects of the blue light-blocking glasses.
Lin et al. assigned 36 participants into groups with the clear lens placebo, low-blocking glasses, and high-blocking glasses [6]. Afterwards, participants performed a 2-hour task on identical computers in similar controlled environments. Researchers used the CFF device and a participant-reported survey to evaluate symptoms of eye strain and fatigue [6]. The CFF depicted significantly less eye fatigue in the high-blocking group compared to the low-blocking and placebo groups. Participant surveys suggested that the high-blocking group reported feeling less pain and itchiness in their eyes after the computer task. However, there was no statistically significant correlation between blue light-blocking glasses and eye strain specifically, based on the participants’ self-reported scores for the intensity of their eye strain symptoms [6]. Therefore, researchers determined that blocking large amounts of blue light may reduce eye strain from screen exposure, but more research needs to be done to determine if this effect is substantial. Awareness of these results can encourage the usage of blue light-blocking glasses to decrease eye pain and itchiness, while further studies can also evaluate its effects on eye strain and the specific amount of blue light blocked by different glasses [6].
Similar to Lin et al., Leung et al. also presented inconclusive results. Leung et al. compared the symptoms of patients wearing blue light-filtering glasses, brown tinted glasses, and a placebo, and found that while blue light filters decrease eye sensitivity, most participants could not detect these changes [7]. A group of 80 computer users wore the lenses for two hours each day for around one month. The participants switched between the lenses during this time period. Researchers performed contrast sensitivity tests on the participants to see how accurately they can read a chart. Researchers use these tests to evaluate how accurately participants could read a chart in which the contrast of each black letter fades into the white background in small increments [7]. This test found no significantly different contrast sensitivity results between the experimental and placebo groups. Based on weekly questionnaires, more than 45 percent of patients reported no changes in their eyesight or eye strain symptoms, while the majority reported no differences between the blue light-blocking glasses and the control lenses [7]. Researchers concluded that analyzing the effects of blue light-blocking glasses is difficult. Spectral transmittance, which evaluates the amount of blue light blocked, showed that the glasses reflected around 10.3 percent to 23.6 percent of harmful blue light [7]. Based on this discovery, researchers found that it is still important to wear these glasses to block the harmful radiation present between 400 and 500 nm in the blue light range, even when participants found no noticeable benefits. The differences between these two studies suggest how these various approaches could lead to similarly inconclusive results.
To compare the two studies, Lin et al.’s research included only 36 participants in a two-hour-long study in identical environments, while Leung et al.’s study had 80 participants and occurred over two months with no supervision [6, 7]. While Leung et al.’s study could analyze long-term effects of the glasses, Lin et al.’s experiment could only analyze the short-term benefits but in a controlled environment. Additionally, Lin et al.’s study only allowed each participant to try on one of the glasses, while Leung et al.’s experiment allowed participants to wear each one of the glasses [6, 7]. As a result, Leung et al.’s study eliminated differences in personal opinion between participants by only evaluating how one group responded to each of the variables. The outcomes of both studies showed how blue light-blocking glasses could relieve eye strain, although more research still needs to be done on this topic.
Ergonomics
While there is conflicting evidence for wearing blue light glasses as a behavioral modification technique, the ergonomic approach shows more promise. To determine the benefits of ergonomics on computer vision syndrome (CVS), Mowatt et al. evaluated the prevalence of eye strain in students at The University of the West Indies (UWI) [2]. Specifically, researchers analyzed how the angle of a computer screen affects eye strain. In this cross-sectional study, 409 students answered a questionnaire related to how often they use a computer, the severity of their eye strain symptoms, and the angle of their screens in relation to their eyes [2]. The results depicted how severe eye strain occurred in 63 percent of the students who look down at their device compared to 21 percent of the participants who keep their device at eye-level [2]. However, the data did not present a relationship between the prevalence of eye strain and the length of time spent on a computer. These results support the use of ergonomic practices, such as keeping a screen at eye-level, to reduce eye fatigue. Increased awareness of such behavioral modification techniques, especially by universities, can prevent eye strain in students [2]. A similar study also uses a survey to analyze practices among individuals who work on computers daily.
Using surveys, researchers analyzed how ergonomics and symptoms of eye strain can be correlated. Office workers answered a questionnaire about eye strain symptoms and workplace conditions [3]. Researchers found that a higher angle of gaze towards a monitor is associated with more CVS prevalence [3]. In addition, looking upwards at a screen should be avoided as it results in muscular strain on the trapezius and neck muscles. This contrasts with the study at UWI, which determined that patients who looked down at their screens, at relatively large angles from eye level, tended to have more strained eyes [2,3]. Based on the results of both studies, placing the screen between eye level and at a small angle of 10 degrees downwards may be the best resolution. Moreover, using a monitor with a filter and adjusting the brightness of an individual’s screen to match that of the environment is correlated with less CVS [3]. Although these results may seem to be solutions for CVS, they are based on surveys rather than controlled studies [2, 3]. Therefore, there is no definite causation between a certain ergonomic practice and eye strain.
Conclusion
When looking at all the possible treatments for eye strain from screen exposure, there are many different medications [1, 4, 5], types of blue light-blocking glasses [6, 7], and ergonomic techniques [2, 3] that can reduce symptoms. O3Fas and the presented botanical formula both show reduction in eye strain symptoms when evaluated with Schirmer’s test for dry eye [1, 4]. The BE study also showed promising results in reducing symptoms of eye fatigue through the CFF test, which focuses more on the temporal processing ability of the eyes [5]. Though blue light-blocking glasses show positive results on the CFF tests and through measured spectral transmittance data, there are mixed results as to whether or not participants detect any changes in eye strain when wearing these glasses [6, 7]. Further testing can be done to evaluate the effects of blue light glasses, such as by examining a larger population or through a longitudinal study. Ergonomic techniques are correlated with less eye strain, according to recent surveys [2, 3]. Clinical trials in controlled environments can show more direct implications of ergonomic practices on eye strain from screen exposure. These treatments combined have the potential to reduce eye strain symptoms, leading to fewer headaches and improved concentration.
References:
- Bhargava R, Kumar P, Phogat H, Kaur A, Kumar M. 2015. Oral Omega-3 Fatty Acids Treatment in Computer Vision Syndrome Related Dry Eye. Cont Lens Anterior Eye [Internet]. 38(3):206-210. doi:10.1016/j.clae.2015.01.007
- Mowatt L, Gordon C, Santosh ABR, Jones T. 2018. Computer Vision Syndrome and Ergonomic Practices Among Undergraduate University Students. Int J Clin Pract [Internet]. 72(1):10.1111/ijcp.13035. doi:10.1111/ijcp.13035
- Ranasinghe P, Wathurapatha WS, Perera YS, et al. 2016. Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors. BMC Res Notes [Internet]. 9:150. doi:10.1186/s13104-016-1962-1
- Kan J, Li A, Zou H, Chen L, Du J. 2020. A Machine Learning Based Dose Prediction of Lutein Supplements for Individuals With Eye Fatigue. Front Nutr [Internet]. 7:577923. doi:10.3389/fnut.2020.577923
- Ozawa Y, Kawashima M, Inoue S, et al. 2015. Bilberry Extract Supplementation for Preventing Eye Fatigue in Video Display Terminal Workers. J Nutr Health Aging [Internet]. 19(5):548-554. doi:10.1007/s12603-014-0573-6
- Lin JB, Gerratt BW, Bassi CJ, Apte RS. 2017. Short-Wavelength Light-Blocking Eyeglasses Attenuate Symptoms of Eye Fatigue. Invest Ophthalmol Vis Sci [Internet]. 58(1):442-447. doi:10.1167/iovs.16-20663
- Leung, T. W., Li, R. W., & Kee, C. S. 2017. Blue-Light Filtering Spectacle Lenses: Optical and Clinical Performances. PloS one [Internet]. 12(1): e0169114. doi:10.1371/journal.pone.0169114
Review: The role of gut microbiota on Autism Spectrum Disorder (ASD) and clinical implications
By Nikita Jignesh Patel, Neurobiology, Physiology, & Behavior ’22
Author’s Note: Ever since I took BIS2C at UC Davis, I was intrigued as to how our gut microbiome plays such a huge role in our homeostasis beyond just digestion – in particular, the correlation between decreased microbiome diversity and allergies we learned about in the lab fascinated me. I recently stumbled upon the term “gut-brain axis” and was in awe as to how this connection between our gut microbes and our brain even exists, and learned that gut microbiome diversity is implicated in a plethora of mental disorders, from depression and anxiety, to autism. I decided to write this review to share my learning of how the gut microbiome can change the brain and potentially contribute to Autism Spectrum Disorder (ASD), because I feel as if this is not a widely known correlation – even as a physiology major, I never learned about the gut-brain axis in my courses. Moreover, the cause of autism is still widely undefined and the gut microbiome may provide a possible explanation for ASD onset in some individuals. I believe a wide range of students will find this upcoming research interesting, but my intended audience is those who research autism or work with autistic individuals, as it may provide an explanation for ASD and seems to be a likely target for clinical therapy for autism in the future. Above all, I want my readers to take away a better understanding of the gut-brain axis and how its imbalance can be implicated in brain disorders like autism.
Introduction
Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental disorder characterized by a range of symptoms including difficulty with communication, social interaction, and restricted and repetitive behaviors that present differently in every individual [1]. Although 1 in 54 children are estimated to be on the autism spectrum according to the CDC [2], the etiology of the condition remains poorly understood. Factors including genetics and certain maternal environmental conditions have been identified as potential contributors to the development of ASD in children, but the exact cause is still unknown [3].
A common comorbidity experienced by ASD individuals is gastrointestinal (GI) problems—including abdominal pain, constipation, and diarrhea —as such, autism research is pivoting towards studying the gut microbiome. [1]. Specifically, a link between the composition of the gut microbiome and brain development has been established in recent years — termed the “gut-brain axis”— and it appears to be the future of autism research. This literature review aims to identify the role of the human gut microbiome on the development of autism-like behavior and investigate whether therapies targeting the gut microbiome can be effective clinical treatments for Autism Spectrum Disorder (ASD). The article will first define the differences observed in gut microbiota between autistic and neurotypical individuals, then discuss how these differences in composition may affect brain development, and finally propose clinical implications targeting gut microbiota that appear promising in the treatment and diagnosis of ASD-related behaviors.
Gut Microbiome of ASD Patients Differ From Neurotypical Individuals
The gut microbiomes of Autism Spectrum Disorder (ASD) patients have defining characteristics that significantly differ from those of neurotypical individuals. The human gut microbiome consists of a diverse array of predominantly bacteria but also archaea, eukarya and viruses that possess unique microbial enzymes to aid humans in digestion and also a variety of other physiological functions [4]. The three phyla Firmicutes, Bacteroidetes, and Actinobacteria [5] encompass the majority of bacteria present in the gastrointestinal (GI) tract that aid in these functions. However, an imbalance between the ratio of Firmicutes to Bacteroidetes bacteria is found in autistic individuals when compared to the microbiome composition of neurotypical subjects; in particular, patients with autism tend to have an overexpression of Firmicutes in their gut [6,7]. Other studies have demonstrated an excess of the Clostridium genus in the ASD microbiome [8] as well as an overexpression of the genus Bacilli in the mouths and gut of autistic individuals [7]. While the cause behind this imbalance is unknown, these findings signify a consistent pattern of microbial imbalance in the autistic gut microbiome. In fact, a Random Forest prediction model, a computer algorithm that can classify large sets of data into subgroup “trees” based on data similarity, was able to distinguish ASD children from neurotypical children with a high degree of certainty from just microbiome sequencing data [7], demonstrating the predictability of this dysbiosis by artificial intelligence.
Figure 1: This illustrates the difference between species richness and species abundance. Species richness, a measure of alpha diversity, informs on how many species are present in a sample. Species abundance describes how many organisms of each species are present.
Along with microbial imbalance—termed dysbiosis—autistic children also tend to have a decreased alpha diversity [7,9], which measures mean species diversity, as well as significantly lower gut species richness [7], the number of species present, when compared to age and sex-matched neurotypical children. One study found that for neurotypical children, alpha diversity, species richness, and species abundance all increased between the age groups 2-3 to 7-11; yet for ASD children, no significant development in microbial composition was observed with increase in age [7]. Since autism has been found to slow brain development as children age [9], this reduced development of the microbiome mirrors the altered brain development characteristic of ASD pathophysiology, proposing an association between decreased microbial diversity and autism.
Due to this observed correlation between dysbiosis and ASD, whether gut dysbiosis is truly causal for autism has come into question. In a preliminary study, Sharon et al transplanted fecal microbiota from autistic donors into otherwise germ-free mice (mice with a sterile gut) and observed their offspring’s behavior compared to offspring of mice inoculated with microbiota from neurotypical donors. Notably, mice with the ASD microbiome— characterized by decreased alpha and beta diversity and decreased Bacteroidetes — exhibited behaviors paralleling those of autism, including repetitive behaviors, decreased locomotion and decreased communication [9]. This demonstrated that gut dysbiosis can in fact induce the behavioral deficits observed in ASD. This is significant evidence toward the theory that gut dysbiosis indeed contributes to ASD – an important finding that changes our current understanding of the etiology of autism.
Figure 2: Above is a visual depiction of the study conducted by Sharon & colleagues, where germ-free mice were inoculated with gut microbiota from either autistic or neurotypical donors. Offspring of the mice transplanted with ASD microbiome were shown to exhibit autism-like behavior.
How Microbiota Imbalance Affects Brain Function: The Gut-Brain Axis
Since the microbial dysbiosis found to be common in ASD patients contributes to behavioral deficits, several different mechanisms have been proposed for how the altered microbial environment in ASD patients can affect brain development.
Intestinal permeability
The microbes that line the GI tract provide structural and protective benefits to our intestines, including stimulating epithelial cell regeneration and mucus production by the intestinal walls. When microbial diversity is decreased, the integrity of the intestinal walls may be compromised which can lead to increased intestinal permeability [8]. This may allow for lipopolysaccharide (LPS), a pro-inflammatory endotoxin that is found in gram-negative bacterial cell walls, to escape out of the GI tract and into the bloodstream. Serum levels of LPS are in fact found to be significantly higher in autistic individuals [12]. LPS causes inflammation in the central nervous system (CNS) and is found to impair cognition and motivation in the mouse model. Specifically, implications for impaired continuous attention and curiosity behaviors, along with modulation of other areas of the brain like the central amygdala have been associated with circulating LPS [11]. Therefore, altered intestinal permeability is a possible mechanism by which dysbiosis modulates brain inflammation, a hallmark of autism that is thought to contribute to its behavioral symptoms.
Microbial metabolites
As gut microbes carry out cellular functions inside their human hosts, they also secrete compounds as by-products of metabolism. Two such metabolites are 5AV and taurine, which are secreted by gut Bacteroides xylanisolvens and other bacteria. 5AV and taurine levels are found to be significantly lower in autistic individuals [13,14] as well as mice transplanted with ASD microbiome [9], likely due to dysbiosis. Both 5AV and taurine are gamma-aminobutyric (GABA) receptor antagonists, meaning that lower levels of these circulating microbial metabolites can alter the inhibitory signaling of GABA in the nervous system [9]. GABA regulates various developmental processes in the brain, including cell differentiation and synapse formation, so dysfunction in GABA signalling is thought to account for ASD symptoms [15]. Oral administration of taurine and 5AV in a mouse model of ASD with an altered microbiome is shown to reduce repetitive behavior and increase social behavior, suggesting that the deficiencies in these metabolites may contribute to the behavioral manifestations of autism [9]. There are other microbial metabolite imbalances in autistic children, including dopaquinone, pyroglutamic acid, and other molecules involved in neurotransmitter production. These imbalances affect brain signaling pathways, and therefore could contribute to the behavioral deficits often present in autistic children. Further, these metabolite imbalances correlate with the levels of certain gut bacteria, further emphasizing the link between the gut microbiome and neurological disorders such as ASD.
Clinical Implications for ASD Diagnosis and Treatment
Today, symptoms of autism are alleviated with behavioral and educational therapy, and no pharmaceutical treatment exists [1]. With the knowledge that the gut microbiome significantly differs in autistic individuals and that these differences are shown to interfere with the nervous system, preliminary research has been done on potential diagnostics and pharmaceutical therapeutics for ASD that target dysbiosis in the gut.
Diagnostics
To date, there is no objective laboratory test to detect Autism Spectrum Disorder (ASD) in children, so autism is primarily diagnosed through a doctor’s evaluation of a patient’s behavior and developmental history. However, the ability of a computer program to distinguish the autistic microbiome from the neurotypical microbiome holds potential for use in ASD clinical risk assessments through analysis of the gut microbiome, and subsequent gut health monitoring interventions for those detected to have ASD-like dysbiosis [7]. The strong association between the presence of certain bacterial species in the mouth and bacteria in the gut — in particular the significant positive correlation between saliva Chloroflexi and gut Firmicutes—may suggest possible oral biomarkers to predict gut microbial diversity [6]. In addition, the overexpression of certain bacteria in the gut have been identified to be associated with certain symptoms like allergies and abdominal pain, opening an avenue to improve the diagnosis process of ASD through the inclusion of a more objective, laboratory-based test [6].
Microbiota Transfer Therapy
Microbiota Transfer Therapy (MTT) is an emerging therapy that aims to replace the gut microbiome of ASD individuals with a more diverse, healthy gut microbiome. One form of MTT consists of a two-week oral vancomycin antibiotic treatment, followed by a bowel cleanse using MoviPrep, and then finally an extended fecal microbiota transplant for 7-8 weeks, administered orally or rectally. In a clinical trial involving autistic children, MTT significantly increased gut bacterial diversity 8 weeks after treatment stopped, along with improving GI symptoms (including abdominal pain, indigestion, diarrhea and constipation) measured through the Gastrointestinal Symptom Rating Scale (GSRS). Significant improvements in behavioral ASD symptoms were found post treatment as well, measured through increases from baseline scores on a variety of exams that evaluate social skills, irritability, hyperactivity and communication, among other behaviors [16]. These improvements in microbial diversity and subsequently ASD-related behavior were all found to have been maintained at follow-up study two years later, indicating that MTT is a safe and efficient therapy that has potential to improve ASD outcomes in the long-term [17]. However, further studies on the efficacy of MTT are necessary to establish this connection, as the above study sample was small and most symptoms and improvements were self-reported.
Probiotics
Because imbalances in the microbiome are correlated with autism, direct administration of bacterial cultures using probiotics seems to be a potential approach to treat ASD behavioral symptoms. Probiotic treatment that included a combination of Streptococcus, Lactobacillus, and Bifildobacterium was found to be effective in improving core behavioral symptoms of ASD, specifically adaptive functioning, developmental pathways, and multisensory processing in autistic children with GI symptoms [18]. Probiotics have been shown to improve symptoms of other mood disorders like anxiety and depression, both of which are associated with dysbiosis and the gut-brain axis [8], warranting further research on probiotics as a treatment for ASD. Therapies that target microbial metabolite imbalances in ASD individuals, like 5AV and taurine, may also open an avenue for future autism research [9].
Conclusion
The gut microbiome contributes to the maintenance of much of human physiology, with involvement in not only the digestive system but also the immune system and the brain. Dysbiosis of the gut microbiome has been found to be prevalent in children and adults with Autism Spectrum Disorder (ASD), and this dysbiosis may be linked to the behavioral symptoms observed. Treatments that target the gut microbiome, therefore, serve to be useful in improving behavioral deficits associated with ASD and should be a consideration for future research with more rigorous experimental design.
References:
- Mayo Clinic. Autism Spectrum Disorder. Accessed July 30, 2021. Available from: https://www.mayoclinic.org/diseases-conditions/autism-spectrum-disorder/symptoms-causes/syc-20352928.
- Centers for Disease Control and Prevention. Data & Statistics on Autism Spectrum Disorder. Accessed July 30, 2021. Available from: https://www.cdc.gov/ncbddd/autism/data.html.
- Fattorusso A, Genova L, Dell’Isola G, Mencaroni E, Esposito S. 2019. Autism Spectrum Disorders and the gut microbiota. Nutrients.11(2):521.
- Kho Z, Lal S. 2018.The human gut microbiome—A potential controller of wellness and disease. Frontiers in Microbiology. 9:1835.
- Thursby E, Juge N. 2017. Introduction to the human gut microbiota. Biochemical Journal. 474(11): 1823-1836.
- Kong X, Liu J, Cetinbas M, Sadreyev R, Koh M, Huang H, Adeseye A, He P, Zhu J, Russell H, Hobbie C, Liu K, Onderdonk A. 2019. New and preliminary evidence on altered oral and gut microbiota in individuals with Autism Spectrum Disorder (ASD): Implications for ASD diagnosis and subtyping based on microbial biomarkers. Nutrients. 11(9): 2128
- Dan Z, Mao X, Liu Q, Guo M, Zhuang Y, Liu Z, Chen K, Chen J, Xu R, Tang J, Qin L, Gu B, Liu K, Su C, Zhang F, Xia Y, Hu Z, Liu X. 2020. Altered gut microbial profile is associated with abnormal metabolism activity of Autism Spectrum Disorder. Gut Microbes. 11(5): 1246-1267
- Mangiola F, Ianiro G, Franceschi F, Fagiuoli S, Gasbarrini G, Gasbarrini, A. 2016. Gut microbiota in autism and mood disorders. World Journal of Gastroenterology. 22(1): 361-368.
- Sharon G, Cruz N, Kang D, Gandal M, Wang B, Kim Y, Zink E, Casey C, Taylor B, Lane C, Bramer L, Isern N, Hoyt D, Noecker C, Sweredoski M, Moradian A, Borenstein E, Jansson J, Knight R, Metz T, Lois C, Geschwind D, Krajmalnik-Brown R, Mazmanian S. 2019. Human gut microbiota from Autism Spectrum Disorder promote behavioral symptoms in mice. Cell. 177(6): 1600-1618
- Hua X, Thompson P, Leow A, Madsen S, Caplan R, Alger J, O’Neill J, Joshi K, Smalley S, Toga A, Levitt J. 2013. Brain growth rate abnormalities visualized in adolescents with autism. Human Brain Mapping. 34(2):425-36.
- Haba R, Shintani N, Onaka Y, Wang H, Takenaga R, Hayata A, Baba A, Hashimoto H. 2012. Lipopolysaccharide affects exploratory behaviors toward novel objects by impairing cognition and/or motivation in mice: Possible role of activation of the central amygdala. Behavioral Brain Research. 228(2):423-31.
- Emenuele E, Orsi P, Boso M, Broglia D, Brondino N, Barale F, Ucelli di Nemi S, Politi P. 2010. Low-grade endotoxemia in patients with severe autism. Neuroscience Letters. 471(3):162-5
- Ming X, Stein T, Barnes V, Rhodes N, Guo L. 2012. Metabolic perturbance in autism spectrum disorders: a metabolomics study. Journal of Proteome Research. 11(12): 5856-62
- Park E, Cohen I, Gonzalez M, Castellano M, Flory M, Jenkins E, Brown W, Schuller-Levis G. 2017. Is taurine a biomarker in Autistic Spectrum Disorder. Advances in Experimental Medicine and Biology. 975
- Pizzarelli R, Cherubini E. 2011. Alterations of GABAergic signaling in Autism Spectrum Disorders. Neural Plasticity. 2011:297153
- Kang D, Adams J, Gregory A, Borody T, Chittick L, Fasano A, Khoruts A, Geis E, Maldonado J, McDonough-Means S, Pollard E, Roux S, Sadowsky M, Lipson K, Sullivan M, Caporaso J, Brown R. 2017. Microbiota Transfer Therapy alters gut ecosystem and improves gastrointestinal and autism symptoms: an open-label study. Microbiome. 5(1):10
- Kang D, Adams J, Coleman D, Pollard E, Maldonado J, McDonough-Means S, Caporaso J, Krajmalnik-Brown, R. 2019. Long-Term benefit of Microbiota Transfer Therapy on autism symptoms and gut microbiota. Scientific Reports. 9(1):5821
- Santocchi E, Guiducci L, Prosperi M, Calderoni S, Gaggini M, Apicella F, Tancredi R, Billeci L, Mastromarino P, Grossi E, Gastaldelli A, Morales M, Muratori F. 2020. Effects of probiotic supplementation on gastrointestinal, sensory and core symptoms in Autism Spectrum Disorders: A randomized controlled trial. Frontiers in Psychiatry. 11:550593
How Poop is Fighting COVID-19
By Laura Gardner, Biochemistry and Molecular Biology ‘22
Author’s Note: With so much information in the media and online about COVID-19, I find many people get lost in, and fall victim to, false information. I want to reassure the Davis community with factual information on how Davis is fighting COVID-19. With UC Davis’ strong scientific community, I was curious what tools were being used to mitigate the spread of COVID-19. In January 2021, I attended a virtual COVID-19 symposium called Questions about Tests and Vaccines led by Walter S Leal, distinguished Professor of the Department of Molecular and Cellular Biology at University of California-Davis (UC Davis). In this symposium, I learned about Dr. Heather Bischel’s work testing the sewer system. This testing is another source for early detection of COVID-19. In combination with biweekly testing, I have no doubt that UC Davis is being proactive in their precautions throughout the pandemic, which made me personally feel more safe. I hope that this article will shed light on wastewater epidemiology as a tool that can be implemented elsewhere.
Dr. Heather Bischel is an assistant professor in the Department of Civil and Environmental Engineering at the University of California, Davis. Bischel has teamed up with the city of Davis through the Healthy Davis Together initiative to use wastewater epidemiology, a technique for measuring chemicals in wastewater, to monitor the presence of SARS-CoV-2, the virus that causes COVID-19 [6]. When a person defecates, their waste travels through the pipes and is collected in the sewer system. In both pre-symptomatic and asymptomatic individuals, their feces will carry the genetic material that indicates the virus is present. This is because SARS-CoV-2 uses angiotensin-converting enzyme 2, also known as ACE2, as a cellular receptor, which is abundantly expressed in the small intestine allowing viral replication in the gastrointestinal tract [1]. This serves as an early indicator of a possible COVID-19 outbreak and leads to quick treatment and isolation, which are important to stop the spread of the disease.
Samples are taken periodically from manholes around campus using a mechanical device called an autosampler. These autosamplers are lowered into manholes to collect wastewater flow samples every 15 minutes for 24 hours. Next, the samples are taken to the lab where they are able to extract genetic material and use Polymerase Chain Reaction (PCR) to detect the virus. Chemical markers that attach to the specific genetic sequence of the virus are added to the sample, which reacts to the COVID-19 virus by fluorescing visible light. This light is the signal that indicates positive test results.
The samples are collected throughout campus, with a focus on residential halls. An infected person will excrete the virus through their bowel movements before showing symptoms. The samples are so sensitive that if even just one person among thousands is sick, they are still able to detect the presence of COVID-19 genetic material. When a PCR test provides a positive signal, the program works closely with the UC Davis campus to identify if there has been someone who has reported a positive COVID-19 test. If no one from the building is known to be positive, they send out a communication email asking all the students of the building to get tested as soon as possible. That way the infected person can be identified and isolated as soon as possible, eliminating exposure from unidentified cases [4].
In collaboration with the UC Davis campus as well as the city of Davis, Dr. Bische has implemented wastewater epidemiology throughout the community. Since summer 2020, Dr. Bische’s team of researchers have collected data which is available online through the Healthy Davis Together initiative [4].
In addition to being an early indicator, this data has also been used to determine trends, which can indicate if existing efforts to combat the virus are working or not [2]. Existing efforts include vaccinations, mask wearing, washing hands, maintaining proper social distancing, and staying home when one feels ill. UC Davis has implemented protocols including biweekly testing and a daily symptom survey that must be completed and approved in order to be on campus.
Wastewater epidemiology has been implemented all over the world, at more than 233 Universities and in 50 different countries, according to monitoring efforts from UC Merced [3]. This testing has been used in the past to detect polio, but has never before been implemented on the scale of a global pandemic. Lacking infrastructure, such as ineffective waste disposal systems, open defecation, and poor sanitation pose global challenges, especially in developing countries [2]. Without tools for early detection, these communities are in danger of having an exponential rise in cases.
“Our work enables data-driven decision-making using wastewater infrastructure at city, neighborhood, and building scales,” Dr. Bische stated proudly in her latest blog post [2]. These decisions are crucial in confining COVID-19 as we continue to push through the pandemic.
Summary of how wastewater epidemiology is used to fight COVID-19
References:
- Aguiar-Oliveira, Maria de Lourdes et al. “Wastewater-Based Epidemiology (WBE) and Viral Detection in Polluted Surface Water: A Valuable Tool for COVID-19 Surveillance-A Brief Review.” International journal of environmental research and public health vol. 17,24 9251. 10 Dec. 2020, doi:10.3390/ijerph17249251
- Bischel, Heather. Catching up with our public-facing COVID-19 wastewater research. Accessed August 15, 2021.Available from H.Bischel.faculty.ucdavis
- Deepshikha Pandey, Shelly Verma, Priyanka Verma,et al. SARS-CoV-2 in wastewater: Challenges for developing countries, International Journal of Hygiene and Environmental Health,Volume 231,2021,113634, ISSN 1438-4639, https://doi.org/10.1016/j.ijheh.2020.113634.
- Healthy Davis Together. Accessed February 2, 2021. Available from Healthy Davis Together – Working to prevent COVID-19 in Davis
- UCMerced Researchers. Covid Poops Summary of Global SARS-CoV-2 Wastewater Monitoring Efforts. Accessed February 2, 2021. Available from COVIDPoops19 (arcgis.com)
- Walter S Leal. January 13, 2021. COVID symposium Questions about Tests and Vaccines. Live stream online on zoom.
Investigating Anthelmintics for Vector Control
By Anna Cutshall, Animal Biology, ’21
Author’s Note: When considering the topic of my literature review and analysis, I wanted to select work that I could continue research on in graduate school. As I entered academia, my career and life experiences had prepared me well for the unique intersection of veterinary medicine, ecology, and epidemiology. I have been on a pre-veterinary track for many years and have worked professionally in the veterinary field for more than three years. As an Animal Biology major and Global Disease Biology minor, my coursework largely centered around the emerging threat of zoonotic and vector-borne diseases. These experiences considered, my primary research interests lie in how we may integrate veterinary medicine into One Health practices to better combat emerging disease threats. In this literature review, I investigate the viability of anthelmintic drugs against arthropod vectors of disease. The use of anthelmintics against arthropods is fairly new, and the pool of current literature is limited but promising. This review was written for those, like myself, who are interested in new approaches to the control of tropical diseases, especially through the lens One Health. I hope to leave readers with a clear picture of what is next for this field, what gaps in the data should be filled, and how we can use information gained in responsible, sustainable ways to combat both emerging and established vector-borne diseases.
Abstract
This literature review analyzes the efficacy of currently available anthelmintic drugs against key disease vectoring arthropods. When comparing effective dosages between different drugs and vector genera, we found that relatively low concentrations are effective against most vectors, but there is evidence to suggest that ivermectin resistance has been established in some species (Aedes spp). The avermectin drug class also displayed limited efficacy over time, as the drugs degrade in vertebrate species faster than the isoxazoline drug class or fipronil. We determined that the current findings related to this method of vector control are promising. However, further research must be conducted before we implement anthelmintics for mass drug administration as a part of integrated vector management.
Keywords: anthelmintics, insecticides, vector, disease vector, mosquito, sandfly, One Health, integrated vector management, mass drug administration
Introduction
Vector-borne diseases threaten the well-being of hundreds of millions of people globally. This is predicted to increase as climate change and human activity facilitate the spread of vector species to previously unoccupied locations. In a press release by the Sacramento-Yolo Mosquito & Vector Control District, it was reported that multiple invasive mosquito species, including Aedes aegypti, had been identified in northern California [1]. Recent literature suggests that these habitual expansions may be due, in part, to climate change as these species are able to adapt to broader regions that are of similar climate to their native regions [2]. The continued spread of these species leaves unprepared countries at risk for outbreaks of the diseases vectored by invading species. Moreover, most vector-borne diseases remain uncontrolled in endemic regions. The most direct way to mitigate the threat of globalizing tropical vector-borne diseases is to control the species that are vectoring them. Unfortunately, traditional insecticide-based methods of vector control have become ineffective due to the emergence of insecticide resistance. In 2012, the World Health Organization identified the status of insecticide resistance as “widespread”, as most of the globe reported resistance in at least one major malaria vector [3]. Traditional spray and topical insecticides have been compromised by such resistance. Therefore, it is essential that new methods of vector control,without acquired resistance, be discovered, evaluated, and implemented.
There are many new methods of vector control currently under evaluation. These include genetically modifying vectors to render them sterile, the use of entomopathogenic fungi and viruses, trapping, repellents, and environmental modification [4]. As we continue to evaluate each method for its efficacy, the Integrated Vector Management (IVM) method may be our best option for the elimination of many tropical diseases. Through IVM, we take careful and integrated approaches to vector control via intersectional communication between Public Health officials, Governments, Non-Governmental Organizations, and communities in which we hope to implement our strategies [5]. IVM calls for multiple vector control strategies, and increasing control efficacy via synergy between control efforts. Unfortunately, the primary tool utilized for the control of adult mosquitoes, insecticides, has lost efficacy over time. This is a result of vector insect populations developing resistance to common insecticides, such as pyrethroids and organophosphates, that are used to control adult mosquito populations. However, there is a reservoir of insecticides that have not been utilized against human disease-vectors, which therefore have minimal acquired resistance . This class is oral insecticides, or insecticides ingested by vertebrates that act when a vector is exposed via blood meal from a treated animal. The use of oral insecticides has been standard in veterinary medicine for years, in the form of flea and tick prevention. Common classes of oral insecticides include avermectins, isoxazolines, and phenylpyrazoles. These compounds have been standard in human and/or veterinary medicine as ectoparasiticides, demonstrating their safety for use in vertebrates. Avermectins, isoxazolines, and phenylpyrazoles have similar modes of action as neurotoxins, with both interrupting the function of GABA-gated chloride ion channels, resulting in insect paralysis [6, 7]. Importantly, there is still diversity within these classes as tools against vector species, as they bind to different sites on the GABA receptors [7, 8]. Investigating the efficacy of these drugs for use as insecticides, against key vectors of diseases such as malaria, zika, west nile virus, leishmaniasis, and African Trypanosomiasis, could be part of the solution to the increasingly urgent problem of insecticide resistance.
Research is currently underway, across the globe, to investigate the efficacy of ectoparasiticides against disease vectors. The question still stands, however, if the approach of oral insecticides is any more effective than the traditional insecticides available. To answer this question, we assessed the current literature regarding the testing of ectoparasiticides against disease vectors, and developed a database of studies testing the efficacy of these compounds against vector insects. This analysis aims to determine the relative efficacy of these compounds to determine if these drug classes are worth consideration for use in vector control and management.
Materials and methodology
To establish a database of the relevant literature, we first mined the scientific literature via the UC Davis Library. Using access granted to undergraduate students, the search terms utilized were input as follows: title/abstract contain “vector” AND “veterinary” AND “control”
AND “arthropod” in the key word function. Papers were then selected for further analysis. These articles were input into an AI-based literature analysis tool, “Research Rabbit”, to identify additional relevant studies [9]. In addition, studies were selected from the works cited of previously selected works. Papers not testing the efficacy of oral insecticides on adult disease vectors were excluded from the study. Additionally, papers without comparable data (did not supply direct mortality or density data) were also excluded.
Each paper was analyzed to extract relevant data on the efficacy of oral insecticides against disease vectors. The data was collated into a Microsoft Excel spreadsheet. Categories selected for further evaluation included: drug type, the concentrations used, associated concentration resulting in 50% mortality (LC50 values), time to mortality, the reduction of vectors present in field study by visual count (resting density), and drug effects on vector fecundity. However, for the purposes of this study, we focused on LC50 and temporal values.
Other categories were not consistent across publications.
When creating data visualizations for comparison of different drug types, R’s “ggplot2” package, “dplyr” package and “esquisse” package were used [10-13]. The categories determined to be best for visual comparison were “Temporal Data” and “LC50” data. After initial visualization was made in R, figures were exported to Adobe Illustrator to edit aesthetically, which was limited to modification of font types and caption content [14]. When creating visualizations for LC50 data, both sandfly and mosquito vectors were compared on the same figure, to compare the efficacy of not only drugs in relation to each other, but also drugs in relation to their efficacy against different disease vectors. When creating the data visualization for this comparison, the drugs “Moxidectin” and “NTBC” were excluded. Moxidectin’s LC50 value was too high to allow for reasonable comparison to other drugs, and NTBC only had a value for tsetse flies (Glossina spp), which were not represented in any other drug. Additionally, the Lutzomyia spp displayed LC50 values too high to be effectively compared to other disease vectors. When visualizing temporal data, only Anopheles spp and Phebotomus spp had enough supporting information in the literature for effective comparisons. There were 5 studies that supplied data for Anopheles spp temporal data and 2 studies that supplied data for Phlebotomus spp temporal data. These temporal data were plotted as Day of Feeding against Mortality, faceted by drug type, and grouped by dose. 2 Figures were created, one for Phlebotomus spp and another for Anopheles spp.
Results
Database Creation
From the initial search in the UC Davis Library system, 15 studies were selected. Then, based on the output from Research Rabbit, an additional 5 studies were selected. Finally, 3 additional papers were identified and integrated into the analysis from the references of the 20 studies. These 23 studies were then evaluated individually from January, 2021 through March, 2021.
We obtained multiple data categories for comparison between the selected papers. Figure 1 displays the summary of the resulting database. Due to the recent nature of this research, resources from which to draw for our database were limited. Table 1 shows a summary of the data types and the number of papers each data type was collected from. Within each paper, some investigated efficacy against multiple vector genuses while others investigated only one. Based on the data we were able to collect, we will be moving forward directly comparing temporal data as well as LC50 data.
Comparing Effectiveness of Dosages Between Drugs
We sought to compare the concentrations of drugs required to be effective against the disease vectoring arthropods studied. Figure 2 displays the LC50 values chosen for comparison as a “lollipop” plot. Within the plot, each “dot” represents a single datapoint taken from a study, and 7 studies were compiled to create the plot. In this figure, we are able to compare 2 major drug classes: avermectins and isoxazolines. The isoxazoline drug class had more available data across insect families, and it is clear that the LC50 value is variable between genuses. Sandflies have more resistance to isoxazolines (especially fluralaner) than mosquito species. Amongst the avermectins, Anopheles spp. Display the most consistent, and relatively low LC50 values. However, Aedes spp. displays higher resistance to ivermectin compared to Anopheles spp.
Comparing Temporal Data
Temporal data involving different insecticides were first to be compared. In temporal data, the “Days Post Feeding (Day of Blood Meal)” represents the number of days after the initial dosing of the vertebrate animals (for example, “Day 3” indicates mosquitos that fed on an animal 3 days after it was given the drug). We were able to create 2 figures for comparing the efficacy of drugs over time at various doses. Doses were represented as variance in color in the figures. Figure 3 displays the efficacy of oral dosing to vertebrates of eprinomectin and ivermectin against Anopheles spp. over time. Both of the drugs in this comparison were of the avermectin class, and neither displayed robust effects on mortality past the 15 day mark after single-dosing of vertebrates with the drugs. Additionally, we observe great variance in the efficacy of ivermectin, even within dosages (that is, mortality varied within dosages between different studies). Unfortunately, mosquito genuses outside of Anopheles did not provide enough data to compare efficacy over time.
Created in a similar fashion, Figure 4 displays the efficacy of oral dosing of vertebrates with fipronil and fluralaner. Here, two separate drug classes were tested for efficacy. While fluralaner (a member of the isoxazoline drug class) acts in a similar mode of action to avermectins, it maintains efficacy over time in Sandflies. Because mosquitos displayed more sensitivity to isoxazolines than sandflies, (Figure 2) one may predict similar, if not more deadly, effects when isoxazolines are tested over time for mosquitos. The drug fipronil displays varying efficacy between doses. Unfortunately, the study involving fipronil did not collect data past 21 days of administration, but it is possible some of the dosages would have remained effective from visual interpretation of the figure. Due to the limited amount of studies investigating the efficacy of oral insecticides, we were not able to compare the efficacy of all drugs over time, as other studies used different methods of efficacy measurements.
Discussion
Based on the findings of our review of currently available literature, oral insecticides certainly show promise as a method of Disease Vector management. As displayed in Figure 2, we are able to determine effective dosages for each drug as a concentration in blood. However, there was significant variance in the data between taxa and between drugs. The highest resistance was observed in Aedes spp. against ivermectin, which could be evidence of acquired resistance due to the common use of ivermectin in humans as an anthelmintic [15]. Another significant variance observed was the relative resistance of sandflies to isoxazolines, requiring approximately twice the concentration or more compared to mosquito species [16]. It is unclear if this effect carries over to other drugs, as there is no available data.
There were also studies analyzed that were not included in the visual data analyses performed. These included studies that investigated the efficacy of isoxazolines against the kissing bug, of nitisinone against the tsetse fly, a field study, and data from otherwise integrated studies measuring the effect of the drugs on fecundity of arthropods [16-22]. The investigation by Loza et al. regarding the efficacy of isoxazolines against the kissing bug showed similar temporal data results to papers investigating isoxazolines against Sandflies, which was visualized in Figure 4 [17]. The isoxazoline drug class, then, has been shown to be effective against 3 major disease vector families. Another drug class also shows promise. A study by Sterkel et al proposes the use of nitisinone (traditionally used in the treatment of hereditary tyrosinemia type 1, a genetic disorder) as an insecticide dispensed to vertebrates, and investigates its efficacy against the African Trypanosomiasis vector, the tsetse fly. This study highlights the importance of looking for alternative methods to vector control, and manipulates a characteristic of a drug originally developed to aid in human disease against disease vectors. The 2021 study found that concentrations above 0.5 micrograms per milliliter in blood impacted survival of feeding tsetse flies significantly, while also studying pharmacokinetics when ingested by mouse models [18]. Pharmacokinetic data supplied by the mouse models in this study may assist in any later calculations for human dosage. No evidence is available on the effectiveness of nitisinone on other disease vectors.
Three studies supplied data involving sublethal effects on adult arthropods, including fecundity. These studies found that there were significant effects on Anopheles spp. fecundity, regardless of vertebrate being dosed and observed across multiple doses [20-22]. There is no currently available data involving the effects of isoxazolines or phenylpyrazoles. Should they be provided, however, they show additional promise as vector management tools. When an insecticide is able to exhibit both lethal and sublethal effects, particularly regarding fecundity, insects that survive the initial exposure produce less offspring than their unexposed peers.
In order for these methods to be effective in Disease Vector management, there would need to be a considerable number of individuals in the population participating to make a significant impact on the burden of vector borne diseases [16, 19]. Mass Drug Administration (MDA) is expensive, and cost is a limiting factor in many of the areas we hope to lower disease burden in. Due to this, and issues related to the accessibility of MDA, it is important that drugs remain effective for an extended period of time. Fortunately, we found this to be the case. As evident in Figure 4, both isoxazoline drugs display extended efficacy on mortality of sandflies over 40 days after initial vertebrate dosage. Additionally, it may be that fipronil displays a similar effect in higher tested dosages, following the trajectory of the available data. Unfortunately, there is limited literature on this subject, so we are unable to say with absolute certainty that these effects would carry over to mosquito species. Figure 3 suggests that the avermectin drug class does not have the same long-term effect on arthropod mortality. For both ivermectin and eprinomectin, mortality dropped below 50% overall after just 14 days from initial dosage. For this reason, the isoxazoline and phenylpyrazole drug classes may be more effective for MDA, although their testing for safety in humans is less extensive (than ivermectin).
Additionally, there is the question of if MDA should be dispensed to humans or livestock. The field study by Poche et al. applied previous findings to the field, dosing cattle in several tribes in Africa and visually measuring the effects on the density of mosquitos found in nearby homes. They observed that the dosage of livestock with fipronil reduced the “resting density” of mosquito species known to feed on both cattle and humans, but did not significantly affect the resting density of particularly anthropophilic species [19]. This study highlights the importance of catering an MDA to the specific species you want to impact by ensuring dosage to vertebrates that it is likely to take a blood meal from.
When considering a drug for use in MDA, the safety of the drug must be copiously studied, and current findings are promising. At the dosages used in the study that were effective against adult arthropods, vertebrates suffered no severe adverse effects attributed to the dosages in all of the studies analyzed. This strongly suggests that these drugs are safe for use in IVM. Additionally, when considering MDA, taking a “One Health” approach will also be key to success. Too often, non-Governmental Organizations have gone into regions with targeted endemic diseases, and neglected to listen to native perspectives on previously used methods of disease control and basic needs. While investigating the efficacy of these drugs is important to protecting communities against vector-borne disease, giving aid to impoverished communities must first address the baseline health of individuals at risk. Only then can we hope to earn the trust of native populations, and continue to help them in sustainable ways. Continuing to thoroughly investigate the efficacy and safety of this sector of vector management before beginning any large implementation will also be essential.
Overall, it can be inferred from the amount of studies performed that there needs to be an enormous amount of research performed before we integrate oral insecticides, especially in humans, into IVM. What we do know, though, gives promise in the face of the insurmountable resistance to traditional pesticides.
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First steps in the development of small-scale 3D printed hydrogel bioreactors for protein production in space travel
By Maya Mysore, Laura Ballou, Anna Rita Moukarzel, Alex Cherry, David Duronslet, Lisette Werba, Nathan Tran, Hannah Mosheim, Stephen Curry, Simon Coelho
Advisors: Kantharakorn Macharoen, Matthew McNulty, Andrew Yao, and Dr. McDonald, Dr. Nandi, and Dr. Facciotti
Author’s Note: My name is Maya Mysore, and I am a team lead on the BioInnovation Group’s Plant Bioprinter project. The BioInnovation Group is a student organization that creates research and leadership opportunities for undergraduates. The Bioprinter project is one of these opportunities.
I joined the BioInnovation group (BIG) in the winter quarter of 2019, as a freshman looking for ways to get involved on campus. I knew I liked research; I had been working in another lab. However, I was looking to explore different aspects of research. I heard about BIG through some friends in my major and went to an information session. There, I tried to join the more tech-based microfluidics project; however, my previous lab experience with cell culture convinced the lead for the Bioprinter project to get me involved in their work. I spent the next couple quarters investigating how to trap viruses in hydrogel. In Fall 2019, I was offered the role of lead. I was shocked, surprised, and a little out of my depth– after all, I had practically joined the project by accident! But I took on the role, excited about the leadership opportunity and the freedom. Now over a year into being project lead, I am planning to transition into the organization’s leadership. However, as a swan song to my time in charge, I wanted to compile all the hard work those involved with the project have accomplished. This paper is a celebration of the work of tens of student researchers over a period of several years. Hopefully, this paper will be the first of many for the Bioprinter project and the BioInnovation Group.
Abstract
As human space exploration expands to include potential settlement on the Moon and Mars, the ability to build shelter, manufacture food, produce medicine, and create other necessities in space will become increasingly important. Currently, the high cost and size constraints of sending payloads into space challenges us to think beyond the traditional manufacturing and agricultural tool-kit. Engineers have proposed that additive manufacturing, particularly 3D printing, is a solution to lower the payload costs and to enable the manufacturing of a variety of products in situ. This study focuses on 3D printing engineered biological cells for the production of biologics (e.g. pharmaceuticals that are living or derived from a biological source). We describe in-progress work to design, build, and test a small and affordable 3D bioprinter capable of printing 3D structured hydrogels that can carry living cells. We provide a general overview of the project, our progress in converting a low-cost and compact 3D printer from printing plastics to printing hydrogels, and preliminary work testing the compatibility of bioink formulations with genetically engineered rice cells that produce and secrete the enzyme butyrylcholinesterase.
Background
As humans continue to explore space and potentially settle in distant locations such as the Moon, Mars, and beyond, it will become increasingly necessary to build shelter, create food, and develop medicine while in space. However, the major costs (roughly $20,000/kg) and size constraints of sending payloads into space create challenges for such long-duration space travel beyond low Earth orbit [1-4]. Challenges include the manufacturing of food, shelter, and even medicine. 3D printing has been proposed as a cost-effective method for addressing some of these challenges, as it might allow the opportunity to ship only the printer to remote sites and to source the majority of the printing materials from the settlement location [5].
Biological systems may also play a large role in this approach. Microorganisms have been envisioned to help construct habitats through biocementation, a process that uses microorganisms to solidify inorganic matter into 3D structures [6-8]. Plants and microbes together are proposed as possible tools for the creation of sustainable ecosystems that recycle and detoxify waste and produce food [9-11]. A purported advantage of biological systems is that they can self-replicate, as each organism carries the full set of genetic instructions to create copies of itself. This means that biological systems could be delivered as light-weight “seeds”, i.e. self-replicating units that can be shipped in small and light quantities and grown to larger quantities upon permanent settlement at remote bases.
We and others envision that the 3D printing of engineered living systems (e.g bioprinting) may prove useful for the manufacturing of biologicals; this includes pharmaceuticals of or derived from a biological source [12]. In this context, the engineered living system serves as an on-demand expandable factory for the production of the biological while the 3D printer serves to produce custom-made culturing and purification hardware that can be produced in the geometries required for specific cells and production sizes. We were interested in exploring this concept and better understanding the challenges associated with the proposed process of drug production through bioprinting. In order to do this, we needed a bioprinter. Depending on their feature sets, commercial bioprinters can cost anywhere between $10,000 and $200,000, which was well outside our budget. Therefore, as a first step, we sought to design, build, and test a low-cost and compact bioprinter that we could later customize and use to explore novel design ideas.
FExisting modalities of bioprinting were considered and four main existing modalities of 3D bioprinting were considered: inkjet, pressure-assisted, laser-assisted, and stereolithography. For a detailed review on this subject, see Li et. al [13]. The major factors that were considered in the selection of a printer were types of usable bioinks, potential for good cell viability, cost, and complexity of the system (e.g. ease with which it can be modified). Inkjet-based bioprinting uses computer controls to drop small drops of bioink onto a surface. This type of printing maintains high short-tem cell viability and is widely available at low cost. However, it is limited in printing materials and creates high thermal and mechanical stress on cells which risks damage to cells and may affect long-term viability. Pressure-assisted bioprinters extrude bioink continuously onto a surface. While the extrusion process is slower and can lower cell viabilities immediately after printing (ranging from 40-80%, compared to 90% for inkjet printing), it allows use of a greater variety of materials and incorporates cells directly into the bioink. Laser-assisted bioprinters use a laser to irradiate a bioink such that the droplets adhere to the desired surface. This method of bioprinting is very precise and results in the highest cell viability; however, it is the most expensive, time-consuming, and has the highest risk of metal contamination. Finally, stereolithography printing uses illumination of a light-sensitive polymer to solidify 3D shapes. This method is fast, cost-effective, and has high final cell viabilities, but it is primarily limited by the need for a light-sensitive bioink, many of which are not biocompatible.
We chose to build a pressure-assisted bioprinter primarily due to practical factors: (a) the availability of low cost and compact fused deposition modeling (FDM) printers that could be used as chassis, theoretically enabling a “simple” swap of printing nozzles and pumps while taking advantage of the existing build platforms and 3D control systems; (b) the easy access to safe and low cost of compatible bioinks, and (c) the ability to incorporate cells directly into the bioink for prototyping.
This paper describes the progress of our project in developing a functional bioprinter. In addition, we describe the chemical assays used to evaluate engineered rice cell viability within hydrogels and these cells’ cell’s ability in gels to produce the pharmacologically-relevant enzyme Butrylcholinesterase (BChE), which is a complex human serine hydrolase enzyme that provides protection against organophosphorus poisoning from toxic agents such as sarin.
Figure 1. This diagram demonstrates the model methodology for seeding the cells into the hydrogel, printing out the cell-gel complex, and extracting the protein of interest from this system.
Methods
Printer selection, modification and testing
Selection of chassis
We sought to find a low-cost and compact FDM printer system that could be reasonably modified to extrude bioink rather than plastic filament. We ultimately selected the Monoprice MP Select Mini 3D Printer V2 because of its high availability, low cost ($250), and relative ease of modification. An accurate open source 3D computer-aided design (CAD) model (https://www.thingiverse.com/thing:2681912) of this printer was already available, making it easier to design new features for this specific unit.
Construction of an bioink extruder
To start converting the 3D plastic printer into a bioprinter, the printer’s original extrusion mechanism was replaced with a standard syringe/syringe-pump mechanism typical of bioprinters [14].
Incorporating the syringe-based bioink extruder required the design and construction of the entire extrusion system. An interchangeable mount was designed to hold the 10 mL syringe on the printer access, as seen in Figures 2b and 2c. In Figure 2b, the interchangeable mount design is shown with a trapezoidal connection piece, allowing the mount to swap between holding the 3D printer plastic extruder and the bioprinter syringe extruder system.
Figure 2. a) Inside of the 3D printer after all electrical components and panels were removed b) 3D printed interchangeable mount used to exchange the plastic extruder and the syringe extruder. c) The hydraulic extrusion system as connected to the bioprinter d) The hydraulic extrusion tubing system
The 10 mL syringe was connected to a hydraulic pumping system through a plastic tube. The hydraulic system is controlled using a Nema 17 Bipolar 40 mm Stepper Motor connected to an 8 mm threaded rod, forming a linear actuation mechanism. Connected to the rod is a 60 mL syringe plunger which is pushed through a 60 mL syringe. A liquid is placed in the 60 mL syringe and the bioink is placed in the 10 mL syringe also with a plunger sitting on top of the syringe. When the motor turns on, this liquid is pushed from the 60 mL syringe through the tubing and into the 10 mL syringe. This system pushes the plunger through the 10 mL syringe and extrudes the bioink onto the printing surface.
A T fitting made from 6 mm brass tubes was attached to the middle of the tubing system in order to remove air bubbles from the tube, as shown in Figure 2d.
Integration of hydraulic motors with chassis
To power the motor for the syringe extruder, the electrical components needed to be rebuilt. With this in mind, an Arduino Mega 2560 was connected with the HiLetGo RAMPS 1.4 control panel and the A4988 stepper motor driver boards using the wiring setup diagrammed in Figure 3.
Figure 3. This diagram shows the wiring for the 3D printer using the Arduino.
The Z-axis switch was then repositioned and mounted to the printer chassis directly under the print head, as seen in Figure 2c.
Firmware
For the firmware, Marlin was selected because it is open sourced and easily modified with the Arduino IDE. After the firmware and electronics were set up, a G code file was needed to determine the print pattern. Cura was used to develop the file due to its compatibility with the Monoprice 3D printer. The Cura profile used with the bioprinter tests followed a cylindrical shape with a square-shaped infill grid. With this information established, the Cura profile was exported as G Code. In the printer design, an SD card is required to flash the firmware and upload the G code to the bioprinter. With the firmware and G code loaded onto the SD card, the bioprinter could be set up to run test prints with the bioink. The final cost spent to make the bioprinter came out to $375. Further information on the process of building the bioprinter can be found at https://www.instructables.com/Low-Cost-Bioprinter/.
Hydrogels
Hydrogels are porous water-based polymers that have many valuable uses, especially in fields such as drug delivery and tissue engineering. Here, we use hydrogels for their ability to selectively trap materials on a size basis, as this is what allows us to trap cells and release the protein of interest. Our hydrogel protocol was adapted from Seidel et al., 2017. Briefly, the hydrogel mixture contained agarose (0.2275% w/v), alginate (2.52% w/v), methyl cellulose (3% w/v), and sucrose (3% w/v). Agarose, alginate, and sucrose were mixed into deionized water at room temperature until dissolved. This mixture and the methyl cellulose powder were then autoclaved in separate containers for 20 minutes at 121 C. Upon completion of the autoclave cycle, methyl cellulose was mixed into the gel. The mixture was then left for 12 to 24 hours in a 2-8 C fridge to allow swelling to occur [15]. After this, the gel was ready to be seeded.
Seeding and Crosslinking the Gels
Transgenic rice cells were supplied by the McDonald-Nandi lab. The cells were genetically modified with the addition of a human BChE gene optimized for rice cell compatibility and cloned into the RAmy3D expression system for transformation into A. tumefaciens to allow insertion into rice cells [16]. This allowed the engineered cells to produce the pharmacologically-relevant BChE protein. The provided cell suspensions were mixed thoroughly via pipetting to obtain even distribution of cells. This suspension was then added directly to the hydrogel in a 50% volume split of cell suspension and gel and gently mixed to distribute cells evenly. To crosslink the gels and create solid structures for later use, a 0.1 M calcium chloride solution was prepared. The hydrogel was loaded into a syringe and deposited into weight boats containing enough CaCl2 solution to half-cover the extruded hydrogel. The hydrogel would then cure in the solution for at least 5 minutes or until the shape solidified. Upon completion of curing, the hydrogel could be removed and used for experiments.
Tetrazolium Chloride Viability Assay on Hydrogels
The TTC (2,3,5-triphenyltetrazolium chloride) assay is a method for testing cell viability. TTC is turned red from a colorless solution in the presence of metabolizing cells, allowing for quantification of cell viability. When used with defined standards and run on a spectrometer, it can be used to monitor cell survival over time.
Preparation of the TTC solution involved mixing 0.4% w/v TTC in 0.05 M sodium phosphate buffer, pH 7.5. Once the TTC solution was prepared, the TTC assay was performed.
5-6 mL of 0.05 M sodium phosphate buffer was added to a 15 mL Falcon tube with cured gel to submerge the cured gel entirely. The gel remained in the solution for 15 minutes. Then the Ellman buffer was removed from the tube and 500 μL of TTC were added to the tube with gel while mixing slightly. This tube was stored in a dark area for 24 hours.
If the gel was not cured, roughly 5 mL of gelled cells were first centrifuged in a 15 mL conical tube at 4500 g for 20 minutes. The supernatant was removed and 1 mL of Ellman buffer was added and mixed. The sample was centrifuged again at 4500 g for 15 minutes, the supernatant was removed, and 500 μL of TTC solution were added to the gel-cell mix. This sample was stored for 24 hours in a dark area.
After the 24 hours period ended, the sample-TTC mix was centrifuged at 4500 g for 15min. The supernatant was removed and the gel-cell mix was washed with 1 mL deionized water. The mixture was re-centrifuged at 4500 g for 10 minutes. The supernatant was removed again and 1 mL of 95% ethanol was added to the gel-cell mix. The sample was transferred to a microcentrifuge tube and placed in a 60C water bath for approximately 10 minutes. The sample is then centrifuged at 21.1 g for 15 minutes to recover the final supernatant. The supernatant was then run on a colorimeter or Tecan and the absorbance value was read at 485 nm. Beer’s law was then used to determine concentration from this value.
Seeded Cell-Ellman BChE Concentration Assay
The Ellman assay was used to measure BChE concentration for a sample at a given time point. This assay uses the kinetics of a color changing reaction to quantify the amount of BChE in solution. When in the presence of specific substrates, BChE turns a colorless solution yellow; the peak rate of this reaction can be determined and used to calculate BChE mass in a sample.
After cells were seeded into a hydrogel complex with a disc shape approximately 7 cm in diameter and 1 cm thick, the complex was suspended in 40 mL sucrose-free nutrient broth (NB-S).
The flask was then covered with a cloth filter and placed in the shaking incubator (37C, 5% CO2, 80 rpm). 50 μL media samples were collected from the flask daily over 14 days and the Ellman assay was run directly following collection of each of these samples.
The Ellman assay protocol was based on the Cerasoli lab protocol, which was adapted from Ellman et al., 1961 [17]. To perform the Ellman assay, a 20 mm stock solution of 5, 5’ – dithiobis-(2–nitrobenzoic acid) (DTNB) was prepared. A 75mM stock solution of S-Butyrylthiocholine (BTCh) iodide was also prepared.
Immediately prior to performing the Ellman assay, the Ellman substrate was prepared. 60 μL of DTNB and 30 μL of BTCh were added to the phosphate buffer in the falcon tube. The tube was temporarily stored in ice with light protection.
Then the Ellman assay was performed. In a 96-well plate, 50 μL of sample containing BChE was were diluted into 0.1 M phosphate buffer, pH 7.4, to ensure the generated? outputted slope readings (mOD/min) would fall in the range of 200-1000 when read for 3-5 minutes at 25 C. This dilution was done by estimating the approximate BChE concentration and estimating the mOD/min based on the expected value. 150 μL of Ellman substrate was added to each sample containing well. The optical density of the sample was immediately read at a wavelength of 405 nm for a total of 300 s (5 min) after the measurement was started.
After collecting data from the assay, Beer’s law was used to determine the concentration of product formed. From that value, we could estimate the mass of functional BChE in the total volume of the sample collected [18].
Results
TTC-Gel compatibility
To measure in-gel cell viability, we evaluated the use of the tetrazolium chloride (TTC) assay. This assay measures metabolic activity in live cells by reducing tetrazolium chloride to red formazan through the process of cell metabolism. Effectively, it provides an indication of how well the cells survive over time. Our team modified the assay for use in gels by including extra Ellman buffer and centrifugation steps to provide more opportunity for cells in the gel to be washed.
Figure 4. This figure shows the results of the TTC assay run on the transgenic rice cells in suspension. The leftmost tube is a positive control showing the TTC assay done on cell aggregates in suspension (i.e. without gel) that have been centrifuged into a pellet after the assay was performed. The middle and rightmost tubes are cells suspended in a hydrogel; the TTC assay was performed on this combination of cells in gels. In each tube, the cells have been stained red from the assay, indicating the presence of metabolic activity. These samples can go on to be washed and suspended in ethanol to obtain a viability data value.
To qualitatively assess how different factors like cell distribution and crosslinking might influence the results of the TTC assay, we performed additional variations of the assay. We first visually examined whether cell homogeneity was impacted by the gel. Then, we performed the TTC assay on E. coli cells alone as a positive control. After that, we tested the effects of non-crosslinked and crosslinked gel to ensure neither condition would prevent the use of the assay. E. coli was used for these tests due to our group’s ability to access it more regularly and grow it more easily than the genetically modified rice cells from Dr. McDonald’s lab. All of these tests together allowed us to determine that cell survival could indeed be measured within the gel, allowing us to monitor culture health over time. This will be critical in future use of the model, allowing us to determine ways to improve cell health and protein output by providing a metric for us to test against.
Homogeneous mixing of biological sample
To determine later TTC accuracy, the first key issue to address was homogeneity of cells in a hydrogel. This would determine whether sectioned off samples of cell-gel complexes would be representative of a whole sample. To ensure that the gel mixing protocol yielded a homogeneous suspension of the cells, we first tested our procedure by mixing E. coli expressing a transgenic green fluorescent protein (GFP) and imaged the suspension under UV light. We expect E. coli to distribute homogeneously in the gel similarly to the transgenic rice cells. This mixture was observed (Figure 5a) and confirmed by visual inspection of a homogeneous mix.
Test of TTC assay with bacterial suspension
To ensure that the TTC assay in later tests would be effective with E. coli, we first tested the TTC assay on an E. coli suspension as a positive control for later tests. We ran the modified TTC assay protocol described in Methods, and observed a color change in the solution. The resultant red solution (Figure 5b) matches the literature expectations for the output of this assay on living cells and indicates the assay is effective for E. coli.
Test of TTC assay with bacteria seeded in hydrogel
After confirming the TTC assay was effective with E. coli, it became important to determine how the presence of gel would affect the assay. We suspended the E. coli cells in the hydrogel and ran the modified TTC assay. The results seen in Figure 4c show the suspension turning red, which visually indicates the presence of cell metabolic activity and the effectiveness of the TTC assay.
Test of TTC assay with bacteria seeded in a crosslinked hydrogel
Upon determining the gel did not qualitatively affect the output of the TTC assay, it became necessary to determine whether crosslinking the gel had any effect on the effectiveness of the TTC assay. We reran the same experiment as the non-crosslinking hydrogel experiment, with the only change being the crosslinking process and the different first wash step. We found that the result of the TTC assay appears to be unaffected by the presence of the crosslinked out layer, as the solution turns red in the same way it does for the positive control and the non-crosslinked gel (Figure 5d).
These experiments allowed us to qualitatively determine whether the TTC assay could be an effective measure of cell viability. They also demonstrated that the introduction of a crosslinked hydrogel will not have visible impacts on measuring cell viability.
Figure 5. Qualitative TTC assays were run on E. coli with the pMax plasmid to test homogeneity within the gel and the effectiveness of the TTC assay in different hydrogel conditions. 5a shows the bacteria mixed homogeneously within the hydrogel, which is visible in the fluorescence that is present homogeneously through the sample. 5b shows the ethanol suspension output for a TTC assay run on a pMax E. coli culture, providing a control for later experiments and showing that the TTC assay is effective for E. coli. The left image is the control and the right image is the test condition. The control is run in the same conditions as the test, except the cells are placed in a 60C water bath for ten minutes prior to adding TTC in order to kill them. 5c shows the output prior to ethanol suspension for a TTC assay on E. coli pMax cells that were suspended in an uncured hydrogel. The left tube is the control and the right tube is the experimental condition. The red color visible in the right tube shows that the presence of the hydrogel does not prevent use of the TTC assay. 5d shows the ethanol suspension output for a TTC assay run on E. coli pMax cells that had been suspended in a cured hydrogel. The left image is the control and the right image is the experimental condition. The red color of the suspension indicates the TTC assay remained effective even with the addition of the crosslinked outer layer of the gel. Throughout this figure, variation in intensity of the redness of the samples is related to variations in time spent in suspension of the TTC solution, with redder samples correlating to longer time.
Initial Attempts at Measuring BChE Production
Our second major goal was to determine whether BChE could be collected from our model system (as seen in figure 1). This would allow us to determine if our model system was an effective way to collect our protein of interest for future space travel applications, as well as confirm that our test for BChE quantity would be effective in this system. To test this, our team ran the seeded cell-Ellman assay as described in methods to assess the amount of BChE that was escaping into the media. We first prepared a hydrogel, mixed the transgenic rice cells in, and cured it into a disc shape roughly 7 cm in diameter and 1 cm in height. We then suspended this cured cell-gel complex in NB-S media to stimulate BChE production, and we kept this mix in a spinning incubator to ensure aeration and adequate diffusion of materials in and out of the gel. Media samples were collected over the course of 14 days and were run with the Ellman assay for BChE detection on a spectrometer. The Ellman assay uses the enzyme kinetics of a color-changing reaction between BChE and a substrate to quantify the amount of BChE present in a sample at a given time point.
It is important to note that this test was intended as a trial run of the system in order to ensure that the assay works and that useful data is being collected. In addition, we sought to assess if BChE could escape from the gel at all. Therefore, no negative control was run and only one run of data was collected (shown in the figure below.) As a result, we cannot conclusively state anything about the data. However, the data does show a trend worth noting for future experimentation. The This is that active BChE concentration in the media increased for the first roughly 100 hours, after which the values dropped off. At the time point marked in figure 5, 96 hours, we see the maximal BChE present. If the unusually low value seen at the roughly 120 hour time point is considered erroneous (which we suspect), the data suggests increased production of BChE over the first 4 days of culture followed by a slow decay thereafter with production ending at around day 8. This provides an early quantitative estimate of the time-dependence of BChE production in this model system. This experiment is a first attempt and will be repeated with various parameter variations in the future.
Figure 6. This plot shows the approximate active concentration of BChE released into the media for various time points over 14 days. Each sample was a 50 μL amount of media pulled from the small scale system model. This figure shows a burst in production of active BChE until the 96 hour time point (denoted with a dashed red line), after which the values drop off. The data point at t=120 hours is most likely an outlier resulting from this data being for one set of samples from one test condition.
Preliminary Bioprinter Testing
The process of building and testing the bioprinter was done in parallel with the TTC and Ellman assay testing. Detailed bioprinter testing has not been performed; however, initial testing of the printer showed its ability to print hydrogel into pre-programmed patterns. The grid pattern seen in Figure 7 was printed into a petri dish containing CaCl2 curing solution. The print shows excess hydrogel accumulation near the edges where the printhead briefly paused and reversed direction. In the center of the print, the lines in the grid averaged 1.25mm +/- 0.4 in width. Further testing and refinement is currently in process.
Figure 7. This shows a test print from our modified 3D printer using the hydrogel described in the methods section and cured in standard CaCl2 curing solution. This structure is described as a lattice shape and will be the primary pattern for future prints.
Discussion
In these experiments we determined that the TTC assay was effective in hydrogels, the Ellman assay showed the ability of protein to be detected from solution, and the bioprinter was able to create the desired lattice shape for later use.
Printer Performance
Our experiments to date have demonstrated our ability to convert a low-cost and compact FDM printer into a preliminarily functional bioprinter. The conversion of the original chassis required the modification of the printhead support, the development of a syringe-based hydraulic pump, and the modification of electronic and software control systems. Preliminary prints indicate that the printer can successfully deposit a programmed pattern with feature sizes in the range of 1.5mm. Existing conventional commercial bioprinters can achieve resolutions of 100-200µm, (some even claim filament diameters as low as 3µm), suggesting that we have room to improve the resolution of our system [19]. In addition to improving the resolution of the prints, we want to explore alternate methods for delivering the CaCl2 curing solution during alginate filament deposition to minimize user interaction and allow complete processing inside a biosafety cabinet; this should allow us to increase sterility during printing and print quality.
Cell Viability
Since it is known that pressure-assisted printing may negatively impact cell viability during printing, a key concern was the resulting cell viability of the system. As a result, our general goal for this phase of the project was to test whether a pressure-assisted bioprinter system could maintain cell viability after extrusion. We adapted the TTC assay for this purpose and tested our protocol to determine the effect of bioink and extrusion on cell viability under conditions mimicking those experienced during bioprinting.
Generally, the TTC assay demonstrated the ability of the assay to cellular viability in the crosslinked hydrogel, despite the unknown nature of how crosslinking affects pore size. Despite this success, the TTC assay remains largely qualitative as it is challenging to get quantitative measurements of cell viability when cells are embedded in a gel. This is further complicated by factors like the heterogeneous distribution of cells (or cellular aggregates) in the gel (see figure 4, rightmost sample). If homogeneity is not maintained, we need to design assays that take into account heterogeneous distribution of cells in the gel. In future experiments, we seek to determine whether samples from a large complex of cells in a hydrogel will provide a representative sample.
In later experiments, additional key variables that may potentially affect viability will be tested. These variables include media composition, culture duration, environmental conditions such as temperature, gel architecture, and the additional variables associated with the printer extrusion process (e.g. pressure, needle pore diameter, etc.). Determining how these specific factors affect viability will allow us to modify the printer design to minimize the drop in cell viability upon extrusion.
Protein production
Having confirmed the effectiveness of the TTC assay in the hydrogel, we moved forward to analyzing BChE production and its diffusion into the media. The assay we adopted allowed us to develop a standard method for data collection that can be used to analyze how various factors impact the cells’ ability to produce BChE. Figure 6, for example, shows that we can measure BChE production and diffusion out of the gel, and that under our preliminary experimental conditions, production peaks at 96 hours and then falls over the next 150 hours. While encouraging, this experiment needs to be repeated with many more samples and replicates to obtain a more reliable assessment of measurement error associated with the assay. Despite needing to replicate the experiment, we are confident that this preliminary experiment answered the core question of whether such a large protein – 85 kDa monomers and 4 units in quaternary form, with a total size of 574 monomers [20] – can effectively diffuse out of the hydrogel and avoid denaturation long enough to be collected and purified.
In addition to replication, future experiments should be explored to further improve protein escape from the hydrogel. These tests could increase the mixing speed to use centrifugal force to free proteins from the gel, increase pore size to create more physical space for protein escape, or print the 3-dimensional lattice structure to increase surface area and allow greater escape. Other relevant variables whose impact on BChE production should be tested include media composition and media changing schedules, culture duration, environmental conditions, gel architecture, and growth temperature. In our initial experiments, plant cells were grown in a shaking incubator at 37C to mimic the environment of protein production in mammalian hosts. However, this growth condition may have stressed the plant cells for which growth at 27C is more typical [16, 21]. This may explain the trend shown in figure 6, where die-off occurs after 96 hours.
Finally, in our current studies, the presence of sucrose in gel formulation (which inhibits BChE production) may have adversely impacted the amount of protein produced. While we expected that overlaying a relatively large volume of sucrose-free media would effectively dilute the sucrose to low levels, the presence of sucrose in the initial formulation could have nevertheless impacted the cells’ initial states and therefore protein production. A followup experiment that more stringently controls for the presence of sucrose in the gel than in the studies described above seems warranted.
Conclusion
In this work, we successfully modified an off-the-shelf pressure-assisted 3D printer into a working bioprinter. In addition, we established that BChE producing rice cells are biocompatible with the different bioink gel formulations and that our assays for testing cell viability and protein production are effective when analyzing the cells within the gel. Having shown that we can print gel, assess cell survival, produce BChE, and quantify its abundance, we next seek to optimize both printer function and the measurement assays for cell viability and protein concentration in ways that provide more quantitative data and more refined control over printed structures. Eventually, we expect that such advances will allow us to optimize protein production itself and ultimately develop a bioprinter suitable for protein production during space travel or in other remote locations.
Acknowledgements
Thank you to the Molecular Prototyping and BioInnovation Lab for the lab space, the BioInnovation Group for the administrative, scientific, safety, and monetary support, the McDonald-Nandi lab for materials and mentorship, and all past, present and future members of the Bioprinter team for contributing to these experiments.
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- Varma A, Gemeda HB, McNulty MJ, McDonald KA, Nandi S, Knipe JM. 2021. Bioprinting transgenic plant cells for production of a recombinant biodefense agent. BioRxiv [Internet]. 2021.02.01.429263. doi.org/10.1101/2021.02.01.429263
- Li J, Chen M, Fan X, Zhou H. 2016. Recent advances in bioprinting techniques: approaches, applications and future prospects. J Transl Med [Internet]. 14:271. doi.org/10.1186/s12967-016-1028-0
- Pusch K, Hinton TJ, Feinberg AW. 2018. Large volume syringe pump extruder for desktop 3D printers. HardwareX [Internet]. 3:49–61. doi.org/10.1016/j.ohx.2018.02.001
- Seidel J, Ahlfeld T, Adolph M, Kümmritz S, Steingroewer J Krujatz F, … Lode A. 2017. Green bioprinting: extrusion-based fabrication of plant cell-laden biopolymer hydrogel scaffolds. Biofabrication [Internet]. 9(4):045011. doi.org/10.1088/1758-5090/aa8854
- Corbin JM, Hashimoto BI, Karuppanan K, Kyser ZR, Wu L, Roberts BA, … Nandi S. 2016. Semicontinuous Bioreactor Production of Recombinant Butyrylcholinesterase in Transgenic Rice Cell Suspension Cultures. Front Plant Sci [Internet]. 7:412. doi.org/10.3389/fpls.2016.00412
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Through War and Peace, These Doves Rock
By Daniel Erenstein, Neurobiology, Physiology & Behavior ‘21
“The diversity of the breeds is something astonishing,” Charles Darwin wrote in “On the Origin of Species.” He was not referring to his famous Galápagos finches. Instead, Darwin opened his foundational work by commenting on various breeds of the domestic pigeon, all descended from a common ancestor: Columba livia. Widely known as the rock dove, this species has adapted to urban environments throughout human history. Over time, we have kept pigeons for fairs, racing, message carrying in wartime, and even scientific research.
Since joining the B3 Lab at UC Davis in 2020, I have contributed to research on this model organism. The B3 name, short for Birds, Brains, and Banter, represents the lab’s main goals: to study rock doves and how stress affects their reproductive behaviors, and to advance culturally relevant science communication research and training. In April, I presented a project on how single parenting affects the amygdala, often considered the brain’s “emotional center,” at the UC Davis Undergraduate Research, Scholarship, and Creative Activities Conference. This research helps us to understand the impacts of single parenting in humans, and it could lead to insights that mitigate stresses felt by single parents and their children.
These photographs were captured in the B3 aviary via iPhone 7 camera during 2020 and 2021.
Lazarus Dies, Lazarus Lives Again
By Jesse Kireyev, History ‘21
Each of these photos captures a landscape in slow degradation. Berryessa, for all the wintergreen beauty that it holds, has experienced horrifying fires numerous times over the past few years. The natural bridge that dominates the landscape of its namesake park in Santa Cruz now remains alone, at risk of collapsing like its sibling did, forever leaving the shoreline empty of its beauty. This risk only grows as sea levels rise and as human interaction puts it at greater risk. The salt flats of the Dead Sea used to be covered in water — now nature struggles to fill the few remaining pools as the sea rapidly shrinks. Captured in these three horizons are the struggles of nature to sustain itself despite the present beauty. For all the tranquility of the Ansel Adams-esque lines jutting forth from the foreground, a great and slow war is playing itself out in the back, often hidden to the gazing eye of the unaware viewer. The horizons both serve as a reminder of the danger that lurks in our future, as well as the distant (and perhaps unreachable) hope of resurrection in the face of annihilation.
1. Berryessa Foothills, Solano, California.
Storm clouds move over the fields and lush wetlands, both morphing into the mountains hugging Lake Berryessa. Just a few months prior, the mountains had been scorched by the dizzying flames of the LNU Lightning Complex Fire, a fire whose smoke blotted out the sun for weeks in two of the largest metropolitan areas in America. The ebb-and-flow of the surroundings give us a stark reminder of just how fast a place can be destroyed and can flourish once again from the ashes. Canon EOS 5D Mark III. April, 2021.
2. West Cliff, Natural Bridges State Park, Santa Cruz, California.
Pelicans and seagulls huddle together as they hunt for fish and fight the buffeting winds. The remainders of the natural bridges, which once dominated the state beach, still serve as a helpful vantage point for the seabirds. Locals hope that this vantage point can survive, even as climate change puts the bridge at greater risk every year. Canon EOS 630, Kodak Tri-X 400TX 35mm film. June, 2017.
3. Dead Sea Salt Flats, Masada, Israel.
The salt flats are all that is left of the once sea-filled expanse below Masada. A combination of climate change and human changes to the environment are driving the evaporation of the Dead Sea, which at current rates is expected to be gone in the next three decades. Sony a700. December, 2018.
Review of recent progress in development of genetically encoded calcium indicators in imaging neural activity
By Lia Freed-Doerr, Cognitive Science, Neurobiology, Physiology & Behavior ‘22
Author’s Note: In fall quarter, I got into contact with the Tian lab in the Department of Biochemistry and Molecular Medicine in order to learn more about optogenetic techniques and the difficulties of in vivo sensing of neural dynamics and, with the mentorship of a postdoctoral researcher, I have learned more about different high-resolution sensors (or indicators) and expanded my interests to genetically encoded sensors of cellular dynamics. As I began learning about various types of imaging sensors, calcium ion (Ca2+) indicators, in particular, stuck out to me due to their variety and depth of development. As I am unable to take part in in-person projects due to COVID restrictions, to ensure my understanding of the topics I was reading about, I began to write this review.
Abstract
Methods of performing neuroscience research have progressed remarkably in recent years, providing answers to many different types of questions. Genetically encoded indicators (sensors) are of particular interest for use in answering questions about neural circuits, cell specific populations, and single cell dynamics. These indicators modulate their fluorescence in different cellular environments and allow for optical observations. Of the various cellular activities that can be measured by genetically encoded indicators, the dynamics of calcium ions (Ca2+) are of interest due to their fundamental importance in neuronal signaling. In this review, we introduce the basic underlying features of genetically encoded calcium indicators (GECIs) including characteristics of fluorescence, an overview of GECI engineering, and a brief discussion of some common variants of GECIs and their uses.
Introduction
Modern neuroscientists have found many ways to analyze the information-carrying neuronal circuits and dynamics within the brain. The continued development of genetically encoded optical indicators, specifically Ca2+ indicators, is particularly promising for analyses of single neurons or neural circuits. Optical fluorescence imaging allows large populations of neurons to be examined simultaneously and avoids major damage to the cells of interest [1]. In particular, measuring the dynamics of Ca2+ can be useful in inferring spiking activity in neurons, as Ca2+ is involved in neuronal action potentials. In this review, we will introduce the basic workings of genetically encoded sensors beginning with a ground-up introduction of fluorescence measurements and the process of engineering genetically encoded sensors. Several Ca2+ indicators will be briefly discussed in order to examine recent progress and how this can impact future studies of the brain.
Mechanics of Fluorescence Indicators
Fluorescence imaging is a valuable tool for visualizing populations of cells. It is relatively non-invasive; but, in order to use optical tools to study the cortex, some surgical procedures must still be performed. A cranial window might be installed in the animal to shine light through; alternatively, an endoscope or fiber optic cable could be installed at the desired depth within brain tissue [2].
Fluorescent proteins (FPs) internally form a barrel-like structure containing the chromophore (also known as the fluorophore), which is a trio of amino acids responsible for the protein’s fluorescence. The chromophore is autocatalytically formed as a post-translational modification, requiring just atmospheric oxygen. Genetically encoded indicators rely on a change in the chromophore environment within the labeling FP. Fluorescence is observed when light of an appropriate wavelength excites the chromophore’s electrons, which then results in the emission of a lower energy photon as the excited electrons return to a lower energy state. FPs are often connected to sensing domains, which induce the change in the chromophore environment after detecting the event of interest (e.g., Ca2+ binding for GECIs). Any number of cellular activities may induce a conformational change such as changes in pH or the binding of a ligand. Sensors can have one or two FPs with partially overlapping fluorescence spectra. Single FP-based sensors are generally preferred as indicators; the green fluorescent protein (GFP), cloned from the jellyfish Aequorea Victoria, is the most commonly used FP for single FP sensors [3]. In systems with two FPs, a Förster or fluorescence resonance energy transfer (FRET) occurs. FRET involves an energy transfer from the higher energy (more blue-shifted) donor FP to the lower energy (more red-shifted) acceptor FP. Genetically manipulating FP systems by circularly permuting FPs (fusing the original termini of the FP and introducing a new opening closer to the chromophore) can improve their performance in sensors by making the chromophore more accessible to the outside environment and, thus, more susceptible to environmental changes [4]. FPs like GFPs are also typically oligomeric in their natural environment (i.e. multiple copies stick together); but, in order to help prevent breakdown and allow for better combination with sensing domains in indicators, FPs must also be mutated to become monomeric [5].
Figure 1: A Jablonski diagram that visualizes an electron’s excitation to a higher energy level by absorption of a photon and subsequent fluorescence emission with energy decay.
To image fluorescent systems, we can use fluorescence microscopy with one or multiple photons (Fig. 2) [2]. In one-photon systems, the fluorophore absorbs energy from a light source and is excited by a single photon. Some energy is lost non-radiatively (without light) resulting in the emittance of lower energy, visible photons from the fluorophore. One-photon systems are relatively inexpensive and fast but can only penetrate tissue to a shallow depth. In contrast, multi-photon microscopy shows more promise for in vivo imaging because of its reduced out of focus emission, light scattering, and phototoxicity. The combination of the energy of multiple photons is required for excitation in such systems.
Figure 2: A diagram outlining the setup for a standard fluorescence microscopy experiment.
Genetic encoding of sensors
To introduce indicator genes into a system, methods like in utero electroporation or viral vectors can be used [6, 7]. DNA promoters or localization sequences can be used to target specific subtypes of neurons in organisms to produce transgenic animals. Transgenic animal genomes that have been modified by artificial bacterial chromosomes, CRISPR, or effector nucleases, and are particularly useful when longitudinal and intensive sampling is required. Genetic changes can be maintained throughout an animal’s lifespan and lines of transgenic animals can be bred for further testing [2]. A recombinase system administered via viral vector, like the popular Cre/loxP system, can be used to achieve high specificity [6]. In the Cre/loxP system, the loxP sequences are placed at specific target sites of genomic DNA. The Cre-recombinase protein can then target loxP sequences to modify the genetic sequence. Two mouse lines, one carrying the gene of interest flanked by loxP sequences, and the other line expressing Cre-recombinase, can be bred to produce mice expressing the gene of interest. The Cre Driver mouse line expressing Cre-recombinase can be designed to only express the gene under certain conditions. To apply Cre/loxP to genetically encoded indicator systems, a viral vector injects the indicator genes into the brain cells of a Cre Driver mouse. The indicator is only expressed where the Cre-recombinase is active. Expression would continue through one animal’s lifetime; to create a line of mice that express the desired indicator, other methods must be used [6]. Through recombinase methods, the development of transgenic animal lines is an area of active improvement.
There are several advantages to genetically encoding indicators over other methods of imaging. There are a wide variety of neuronal events that can be observed by constructing indicators from proteins that respond to cellular events, including changes in neurotransmitter concentrations, transmembrane voltage, Ca2+ dynamics, and pH [1]. Genetic encoding also allows for selective sampling of cells based on genotype. Selective sampling is not possible with chemical dyes, nor is the viewing of the evolution of neuronal dynamics during learning or development processes [8, 1]. Similar to chemical dyes, genetically encoded indicators allow for the imaging of brain activity in neurons in vitro and in animals [9]. Neurons have the machinery implanted within them to automatically report cellular dynamics of interest.
There are several different broad classes of genetically encoded indicators that are based on the dynamics of the action potential [7]. Genetically encoded voltage indicators (GEVIs) operate based on the membrane depolarization that occurs during action potentials. Other indicators, like pH and neurotransmitter sensors, detect vesicular release. Genetically encoded pH sensors (GEPIs) react to the decrease in acidity as vesicles fuse with the membrane, and genetically encoded transmitter indicators (GETIs) are used to visualize the release of neurotransmitters into the synapse [1]. Genetically encoded calcium indicators (GECIs) operate based on the rise in cytosolic Ca2+ during an action potential; however, they do not directly measure spiking activity. When an action potential occurs, Ca2+ floods into the cell. Ca2+ influx is important because calcium ions are crucial for the release of neurotransmitters from vesicles, which then go on to produce signals in other neurons. More mild calcium ion dynamics are always present in neurons, even in a resting state. Among these various classes, GECIs have been perhaps some of the most developed of these indicators and, thus, some of the most promising.
Engineering genetically-encoded calcium indicators
Performance Criteria
As GECIs are engineered, many performance criteria must be considered. Tradeoffs often occur between the various important qualities of an indicator’s performance [10]. As we optimize the indicator to produce a desired result in one criterion, another criterion often decreases in quality. Thus, development of sensors optimized for specific applications is continuous. Some of these criteria are affinity, sensitivity, kinetics, localization, and photophysical characteristics.
Affinity, represented as the dissociation constant Kd, describes what percentage of the indicator is unbound given a particular concentration of ligand.
Specificity refers to the indicator system’s ability to respond only to the target of interest, as opposed to perhaps similar molecules.
Sensitivity is usually represented by ΔF/F0, the fractional fluorescence change, which is the fluorescence signal change over a change in concentration of the target molecule. It can also be represented by signal-to-noise ratio (SNR), the relative difference between the signal of interest and background noise.
Kinetics is the rate of change in fluorescence intensity of the indicator in response to the change in ligand concentration. There tends to be a tradeoff between affinity and kinetics [8].
Photophysical qualities like brightness, photostability, and photoswitching behaviors are also important considerations. In general, brighter or more intensely emitting indicators are desired. Photostability is inversely proportional to the rate of photobleaching (the damaging of the FP so that it becomes unable to fluoresce). Additionally, some indicators have broader ranges of excitation than others, or may change their intensity or sensitivity in different light conditions, which would limit usage.
GECIs are some of the most widely used genetically encoded indicators in vivo because of their relatively high SNR and improved properties like brightness, photostability, and dynamic range [2]. However, there are still numerous obstacles to be faced in designing GECIS, and only certain variants have faced success in vivo.
Engineering GECIs
Genetically encoded indicators generally are composed of an analyte-binding (sensing domain) and a fluorescent protein (reporting domain), though there are additional peptide complexes that assist in changing the conformation of the system [2]. Upon the occurrence of a sensing event, the sensing domain undergoes a conformational change which, in turn, induces a conformational change in the FP, resulting in fluorescent activity. Engineers of GECIs use two different strategies for constructing reporting domains: FRET-based indicators and single FP-based indicators [7]. When Ca2+ binds to FRET-based indicators, the spatial relationship between the donor and acceptor FPs changes so that there is a transfer of energy from the donor FP to the acceptor FP [2]. One family of indicators, Cameleon, has had some success. In this family, the sensing and peptide complex is located between two FPs with overlapping spectra. FRET-based indicators’ SNR tends to be lower, meaning it is harder to isolate the activity of a neuron from background noise. Because of these drawbacks, we mostly examine the engineering of the more commonly used single FP-based GECIs.
There are two popular designs among developers of single FP GECIs [8]. One is based on one of the earliest lines of calcium indicators, GCaMP. GCaMP consists of a circularly permuted green fluorescent protein (cpGFP) inserted between the Ca2+-binding protein, calmodulin (CaM), and another peptide called RS20, which binds CaM upon Ca2+ binding. When CaM binds Ca2+, a conformational change is induced in the cpGFP and the sensor fluoresces [10, 11]. Another recent design, the NTnC family of indicators, inserts a calcium-binding domain into a split FP [8]. Unlike GCaMP-type indicators, NTnC indicators display an inverted fluorescence response upon calcium binding (i.e., fluorescence decreases upon Ca2+ binding). They are less optimized than GCaMP variants, but it is hypothesized that their lesser Ca2+ binding capacity would interfere less with normal calcium dynamics.
Figure 3: A basic representation of the GCaMP structure.
There have been efforts to expand the color variants of GECIs. In particular, there has been much effort to develop red-fluorescing GECIs because longer red wavelengths reduce phototoxicity and have better tissue penetration [12]. However, there have been many obstacles to producing red-fluorescing GECIs. Unlike GFP, inserting calcium binding domains into red fluorescent proteins (RFPs) disrupts folding and chromophore maturation [8]. A more popular design choice is to replace the GFP in a GCaMP-style indicator with an RFP and optimize the sensor for a new FP [1].
GECIs are improved iteratively through directed evolution and linker optimization between the cpFP and the sensing domains. Site-directed mutagenesis can be used to mutate specific locations to produce novel variants. In the development of one variant of GCaMP, mutations were specifically introduced in the calcium-binding domain-cpGFP linker in a GCaMP5 scaffold to increase sensitivity [11]. Using directed evolution, mutations are randomly introduced. Then, upon testing for desired effects, the variants that produced the best results may be preserved and propagated. This process may repeat many times, producing increasingly successful indicators as the best-performing mutations survive across generations.
Challenges
Genetically encoding indicators, as a rule, comes with challenges. If we choose to use viral infection as our genetic encoding scheme, consideration must be taken to the many viral serotypes, which have varying levels of efficiency and can be toxic. Furthermore, in utero electroporation can be unpredictable, and transgenic animals may not express indicators at sufficiently high levels to be useful [1].
Sensors may affect the natural dynamics of their measured systems, affecting accuracy of results. GECIs, particularly GCaMP-based designs, may interfere with regular Ca2+ dynamics and gene expression [8]. This interference is likely due to interactions between the calcium-binding sensing domain with native proteins and the lack of availability of calcium once bound to the indicators. There have been efforts to improve and modify the calcium-binding domain so that it can bind fewer Ca2+ or otherwise improve affinity so that the indicator operates at lower concentrations of calcium.
There is also difficulty in using these indicators in vivo [2]. Especially in the mammalian brain, the SNR is highly decreased due to the amount of background noise. This reduced SNR is putting aside the level of breakdown that naturally happens in vivo vs. conditioned, cultured environments. Although many indicators have improved structural integrity in vivo, there are many that still cannot be used in living organisms.
Progress in GFP-based GECIs
There has been much development in the GCaMP series as variants are continuously improved by site-directed mutagenesis and computational design efforts [2]. The jGCaMP7 series, built from the GCaMP-6 series, provides a good example of optimization of indicators for different purposes: jGCaMP7f is optimized for fast kinetics, jGCaMP7s is optimized for high sensitivity (though it has slower kinetics), and jGCaMP7b is optimized to have a brighter baseline fluorescence [11]. All of these indicators are based on the same base scaffold but differ drastically in performance because of just a few mutations in the CaM-binding peptide, the GFP, the CaM domain, or the linkers between domains.
Progress in RFP-based GECIs
RFP-based GECIs have important advantages over GFP-based ones. Beyond the importance of color variety in tracking distinct populations of cells at once, red GECIs are also promising for reducing phototoxicity and allowing deeper imaging [12]. There are many promising RFP-based GECIs being developed, though they are generally dimmer than GFP-based indicators and may display photobleaching behaviors under blue light [1]. In particular, there are R-GECO1 variants like jRGECO1a, the RCaMP series, and, perhaps most promising, K-GECO1 [12]. There are three widely used RFPs from which red GECIs are developed; each red indicator family was generated from different RFPs. K-GECO1 has shown particular promise as it works at a distinct spectral range, allowing researchers to simultaneously work with other indicators in multicolor imaging experiments, and it also shows minimal fluorescent noise [9].
Designs of red GECIs often expand on the GCaMP design–for example, K-GECO1 follows a similar design of sandwiching the circularly permuted FP between the Ca2+-sensing domain, CaM, and a CaM-binding peptide [12]. Switching the GFP in GCaMP with an RFP comes with engineering challenges of linker optimization and preventing the breakdown of the sensor. The increased penetrative depth of red GECIs has been used to image subcortical areas like the hippocampus or medial prefrontal cortex relatively noninvasively, demonstrating the applicability of GECIs in neuroscience research [13].
There are other FP-based GECIs in development, but of particular interest is the development of near-infrared GECIs, whose spectral distinction from other indicators would help prevent photoswitching when used with optogenetic tools [8, 14].
Uses and Applications
The applications of GECIs are varied and powerful. The use of genetically encoded indicators allows for the analysis of cells of a specific type or subpopulation as they select for specific genetic qualities. The first transgenic mouse line expressing GCaMP2 in the cerebellar cortex was generated in 2007 and has allowed for characterization of certain synapses [6]. GECIs have been used to provide single-cell resolution to the decades-long study of various topographic maps in the brain and to track the communication of neural circuits [2]. In rats, GECIs have been used to monitor neural population behavior during motor learning tasks and observe the response of cells to sensory deprivation in the primary visual cortex after retinal lesion. They allow examination of ensemble and single cell-scale neural events at more and more temporally precise levels. Broadly, and perhaps more importantly, they are often used in conjunction with optogenetic and other experimental methods that allow for the inference of causation. In using these indicators, the stimulation techniques used in optogenetic experiments can also involve precise tracking of calcium or other dynamics in cells of interest [8]. These experimental approaches have caused excitement as they allow for the examination of behaviors of cells or whole organisms upon physical stimulation of even just single cells. The continued expansion of these approaches is promising.
Conclusion
Many researchers are devoted to developing new and distinct calcium indicators based on existing indicator series. With more GECIs than ever available to neuroscientists, there is some challenge in choosing which is best suited to the exploration of a particular question. With the continuing development of mouse lines and methods of genetically encoding more potent indicators with high temporal resolution, GECIs will continue to be an increasingly important tool within the neuroscientist’s toolkit that allows for population or single-cell imaging with greater resolution than ever before.
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COVID-19 survivors can retrain their smell to enjoy food and wine again
By Daniel Erenstein, Neurobiology, Physiology & Behavior ‘21
Author’s Note: Last spring, I enrolled in the inaugural offering of the University Writing Program’s wine writing course. Our instructor, Dr. Alison Bright, encouraged us to report on topics of personal interest through our news stories on the wine industry, viticulture, enology, and more. In this article, which was prepared for an audience of general science enthusiasts, I examine how biologists are making sense of a puzzling COVID-19 symptom — anosmia, or loss of smell — and what COVID-19 patients with this condition can do to overcome it. Eighteen months into this pandemic, scientists continue to study cases of COVID-19-related anosmia with dreams of a treatment on the horizon. I hope that readers feel inspired by this article to follow this in-progress scientific story. I extend my appreciation to Dr. Bright, who throughout the quarter shared approaches to rhetorical awareness that elevated my grasp of effective writing.
Image caption: Anton Ego, the “Grim Eater” from PIXAR’s Ratatouille, is reminded of his childhood by Remy’s rendition of ratatouille, a Provençal dish of stewed vegetables.
With a single bite of Remy’s latest culinary creation, the eyes of Anton Ego, a notoriously harsh food critic, dilate, and Ratatouille’s viewers are transported back in time with Monsieur Ego. The meal — a simple yet elegant serving of ratatouille, accompanied by a glass of 1947 Château Cheval Blanc — has triggered a flashback to one singular moment, a home-cooked meal during his childhood. The universal charm of this enduring scene resonates; in Ego’s eyes, many recognize how our senses of smell and taste can impact a culinary experience.
Imagine how a real-life version of this scene might change for the millions of COVID-19 patients who have lost their sense of smell [1]. Anosmia, the phenomenon of smell loss, has become one of the more perplexing COVID-19 symptoms since first observed in patients during the earliest months of the pandemic [2].
What happens when we lose our sense of smell? During the pandemic, scientists have studied smell loss, which affects more than 85 percent of COVID-19 patients according to research published this year in the Journal of Internal Medicine [3]. In fact, anosmia is so common in COVID-19 patients that physicians were offered guidance for testing olfactory function as an indicator of infection last year [4].
To simplify studies of these complicated senses, taste and smell are often examined independently of one another, even though these senses are usually experienced simultaneously.
“Smell is just — it’s so crucial to taste, which means it’s really crucial to everything that I do,” said Tejal Rao, a New York Times food critic, in a March episode of The Daily [5]. “And it’s really difficult to cook without a sense of smell if you’re not used to it. You don’t know what’s going on. It’s almost like wearing a blindfold.”
Rao, who lost her sense of smell in mid-January after contracting COVID-19, began to search for answers to this mystery from scientists. Rao’s journey started with TikTok “miracle cures” and other aromatherapies — unfortunately, they were too good to be true — but she eventually discovered the work of Dr. Pamela Dalton, a scientist at the Monell Chemical Senses Center in Philadelphia [6]. At the center, Dalton studies the emotions that are triggered by our sense of smell [7].
During simple colds or viral infections, smell is normally affected when the molecules in food and other aromas are physically blocked off from chemoreceptors in our nose by congestion. Scientists have also cited Alzheimer’s and Parkinson’s diseases, head trauma, and chemotherapy as triggers for anosmia [8]. But a separate phenomenon was occurring in the case of COVID-19.
“COVID is different in that way, because most people who lost their sense of smell did so without having any nasal congestion whatsoever,” Dalton told Rao during an interview.
One study published in October of last year by Dr. Nicolas Meunier, a French neuroscientist, aimed to investigate how the SARS-CoV-2 virus, which causes COVID-19, may disrupt sustentacular cells [9]. These structural cells express the ACE2 receptor, which the virus hijacks to gain entry into our cells, at higher levels [10]. Sustentacular cells support the specialized neurons that transmit signals from the nose to the brain.
When Meunier and his team at Paris-Saclay University in France infected hamsters with the virus, tiny hair-like projections known as cilia on the surfaces of olfactory neurons began to peel back from sustentacular cells. This disruption is a possible explanation for the difficulties with smell that COVID-19 patients experience.
If it is true that damage to sustentacular cells causes anosmia, loss of smell is not an irreversible brain condition. In this case, the poor connection between incoming odors and brain networks that typically process these stimuli is at fault, not direct damage to the brain itself. The sudden onset of smell loss in COVID-19 patients supports this thinking.
“It was just like a light bulb got turned off or a switch got flicked to off,” Dalton said. “And one moment they could smell. And the next moment, nothing smelled.”
But because olfactory support cells regularly regenerate, this loss of smell is only temporary, which allows for retraining of our senses. Two months of smell training, also known as olfactory training, allowed Rao to regain her sense of smell.
Olfactory training gradually exposes patients to particularly strong smells. Spices such as cinnamon or cumin, for example, were perfect for Rao’s first smell training session [5], and AbScent, a British charity offering support to patients with anosmia, sells kits with rose, lemon, and eucalyptus [8]. Scientists have found that recurring exposure to these strong scents gives the brain time to recalibrate its networks, a feature known as neuroplasticity [11].
But “you don’t just go from hurt to healed overnight,” Rao said. “It’s more like adjusting and learning how to live in a new space. That’s really just the beginning.”
Our chemical senses have the power to satisfy, to inspire, even to cause our memory to reveal itself, as 20th-century French author Marcel Proust observed in his seven-volume novel À la recherche du temps perdu, or In Search of Lost Time. Researchers have even speculated that our sense of smell can facilitate learning in other sensory domains, including vision [12].
While scientists further investigate how coronavirus causes loss of smell, olfactory training can provide an avenue in the meantime for COVID-19 patients to recover this crucial sense. Indeed, many patients are “in search of lost time,” and smell training can help them to once again experience food and wine in its sensory entirety.
References:
- Allen J, Almukhtar S, Aufrichtig A, Barnard A, Bloch M, Cahalan S, Cai W, Calderone J, Collins K, Conlen M, et al. 2021. Coronavirus in the U.S.: Latest Map and Case Count. New York (NY): New York Times; [accessed 28 July 2021]. https://www.nytimes.com/interactive/2021/us/covid-cases.html.
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- What COVID 19 is teaching us about the importance of smell, with Pamela Dalton, PhD. 17 Mar 2021, 33:31 minutes. American Psychological Association; [accessed 28 July 2021]. https://youtu.be/0pG_U13XDog.
- Schoch D. 2021. Distorted, Bizarre Food Smells Haunt Covid Survivors. New York (NY): New York Times; [accessed 28 July 2021]. https://www.nytimes.com/2021/06/15/health/covid-smells-food.html
- Bryche B, St Albin A, Murri S, Lacôte S, Pulido C, Ar Gouilh M, Lesellier S, Servat A, Wasniewski M, Picard-Meyer E, et al. 2020. Massive transient damage of the olfactory epithelium associated with infection of sustentacular cells by SARS-CoV-2 in golden Syrian hamsters. Brain Behav Immun. 89(2):579–586. https://doi.org/10.1016/j.bbi.2020.06.032.
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- Kollndorfer K, Kowalczyk K, Hoche E, Mueller CA, Pollak M, Trattnig S, Schöpf V. 2014. Recovery of Olfactory Function Induces Neuroplasticity Effects in Patients with Smell Loss. Neural Plast. 1–7. https://doi.org/10.1155/2014/140419.
- Olofsson JK, Ekström I, Lindström J, Syrjänen E, Stigsdotter-Neely A, Nyberg L, Jonsson S, Larsson M. 2020. Smell-Based Memory Training: Evidence of Olfactory Learning and Transfer to the Visual Domain. Chem Senses. 45(7):593–600. https://doi.org/10.1093/chemse/bjaa049.
Surviving COVID-19: Variables of Immune Response
By La Rissa Vasquez, Neurobiology, Physiology & Behavior ‘23
Author’s Note: In this paper, I analyze autopsy reports conducted on deceased COVID-19 patients and supply a breakdown of the body’s immune response. The purpose of this paper is to provide a more generalized synopsis of how the body is affected by the virus from the onset of infection to the escalating factors that contribute to cause of death. COVID-19 and SARS-CoV-2 are referenced countless times throughout this paper, but they should not be used interchangeably. The name of the pathogenic virus is “Severe Acute Respiratory Syndrome Coronavirus 2” (SARS-CoV-2), and the name of the illness is called COVID-19 and is the common usage in forms of discussion. This paper only scratches the surface of the virus’s complexity and its effects upon the body and societies around the world.
Introduction
On December 31, 2019, the first case of the novel coronavirus was reported in Wuhan, China [1]. The first case of the virus reported in the United States was on January 22, 2020 [2]. Within 22 days, the Coronavirus had traveled across the Pacific to wreak havoc upon countries woefully unprepared. Within a year, COVID-19 has managed to bring some of the most powerful countries in the world to heel. Economies and healthcare systems across the world continue to be devastated by an adversary only 60 to 140 nanometers in diameter [3]. On February 11, 2020, the International Committee on Taxonomy of Viruses (ICTV) formally identified the virus as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). On March 11, 2020, the World Health Organization classified COVID-19 as a worldwide pandemic and global health crisis [4]. As of May 2021, the CDC has confirmed that the U.S. has over 32 million cases. Healthcare systems across the nation and around the world are overwhelmed by the number of infected patients. Many of them perish due to either a lack of resources or accurate and efficient testing.
SARS-CoV-2 Viral Pathogenesis
Humans have two levels of immunity. Innate immunity is the body’s first line of contact and defense against invading pathogens. Adaptive immunity learns and remembers how to effectively target and eliminate these pathogens.
Innate Immunity
Our innate immune system is composed of barrier tissues and cells specialized for defense against pathogens [5]. Barrier tissues are the first line of defense, and inside barrier tissues reside sentinel cells, which are capable of consistently recognizing repeated exposure to pathogen associated molecular patterns (PAMPs). The sentinel cells release proinflammatory mediators like cytokines, chemokines, or histamines and circulate within the blood vessels inviting more immune cells from the surrounding tissue into the bloodstream [5]. Cells such as neutrophils or monocytes differentiate into macrophages and migrate from the bloodstream and phagocytose (eat) the pathogens. Neutrophils will undergo programmed cell death, referred to as apoptosis. Macrophages will continue to phagocytose the rest of the pathogens and restore homeostasis by consuming the dead neutrophils [5].
Infection occurs when these viral pathogens in respiratory droplets from a sneeze or a cough enter a person’s mouth, nose, or eyes and attach to the ACE-2 receptors in the nose, throat, and especially the lungs. Like any virus, SARS-CoV-2 cannot replicate on its own and instead hijacks the body’s own cellular machinery. The virus inserts its own genetic information into the host cell to produce more copies of itself until the cell bursts and dies, spreading more of the virus around the body to infect more cells [6]. Infection of the host cell consists of the following five steps: attachment, penetration, biosynthesis, maturation, and release. Once a virus binds to host receptors (attachment), it enters host cells via endocytosis or membrane fusion (penetration). Once the viral contents are released inside the host cells, viral RNA are transported by protein molecules in the host cell’s cytoplasm and travel into the nucleus for replication via the nuclear pore complex (NPC). Viral mRNA then makes viral proteins (biosynthesis). Lastly, novel viral particles are made (maturation) and released [7]. This innate immune response is not as effective against SARS-CoV-2 due to the strength of the various proteins displayed in Figure 1, an ultrastructural morphology rendering, provided by the Centers for Disease Control and Prevention (CDC) Image Library on February 10 [8].
Figure 1
The SARS-CoV-2 virus contains “M (membrane), S (spike), E (envelope), and N (nucleocapsid)” proteins, which envelop the virion and act as a defensive shield [9]. The S or Spike viral surface protein, which consists of two subunits, S1 and S2, binds to the angiotensin converting enzyme 2 (ACE2) receptors of the host cells [7]. The primary role of ACE2 is the breakdown of the angiotensin II (ANG II) protein into molecules that neutralize its harmful effects. ANG II is responsible for increased inflammation and death of alveolar cells in the lungs, which reduces oxygen uptake. When the S (spike) protein of SARS-CoV-2 binds to the ACE2 receptors, they inhibit ACE2 from doing its job of regulating ANG II, allowing ANG II to freely damage tissue in the lungs. These ACE2 receptors are naturally present on the surface of the lung’s epithelial cells and other organs throughout the body, but the virus’ S protein uses these receptors to penetrate the cell membrane and replicate inside host cells. The N (nucleocapsid) protein is another viral surface protein of SARS-CoV-2, which inhibits interferons (IFN1 and IFN-β) responsible for cytokine production [10]. But if the signals for regulating proinflammatory response are disrupted by the pathogen’s surface proteins, the innate immune response becomes hyperactive and self-destructive. A malfunctioning innate immune response also compromises an adequate adaptive immune response [9].
Adaptive Immunity
Adaptive immunity consists of B-cell and T-cell responses. B-cells produce antibodies to trigger an immune response, while T-cells actively target and eliminate infected cells.
B-Cell Response
The innate immune response is not particularly equipped to combat pathogens that are especially complex and vicious because the innate immune response is non-specific and will attack anything it identifies as an invader. The adaptive immune response can target pathogens more precisely and powerfully by using proteins called antibodies, which are produced by B-cell lymphocytes that bind to antigens on the surface of pathogens [5]. Adaptive immunity can more efficiently handle foreign pathogens, like a virus, because antibodies can see through the debris of proteins and dead cells left by the cytokine storm. Antibodies uniquely bind to antigens, acting as a beacon for the adaptive immune response to converge on the invading pathogen [5]. More importantly, adaptive immunity has memory and learns how to become more effective by retaining its response to pathogens so that it can be even quicker at eliminating them after repeated exposure [5]. Widespread pandemics like COVID-19 occur because of a lack of protective antibodies in populations that have never been exposed to or vaccinated against the specificity of SARS-CoV-2 [5]. Figure 2 depicts the four ways in which antibodies attack pathogens: neutralization, complement fixation, opsonization, and antibody dependent cellular cytotoxicity.
Figure 2
Figure 2 – “Immunopathogenesis of Coronavirus Disease 2019 (COVID-19)” [3].
Neutralization is the process by which antibodies immediately bind to the surface antigens of a pathogen and block their S protein from attaching to the receptors of healthy cells, thereby neutralizing the virus’ ability to attach and insert its genetic information. Complement fixation occurs when antibodies are responsible for inviting complement proteins to bind to the antigens of the pathogen. This process coats the pathogen in attack proteins that can either initiate the complement cascade leading to cell lysis, the breakdown of the cell, or it can induce the third stage, opsonization. During opsonization, proteins called opsonins bind to the invading pathogen, acting as markers for phagocytotic cells like macrophages to identify and consume the pathogen. Lastly, antibody dependent cellular cytotoxicity (ADCC) is the process by which antibodies recognize the antigen of a pathogen and signal for natural-killer cells (NK cells) to release cytotoxic molecules which kill off the virally infected cell [5].
T-Cell Response
T-cell lymphocytes are produced by the bone marrow and mature in the thymus. They form the basis of cellular immunity because they directly attack foreign pathogens. Consequently, they are more effective than innate immune or B-cell responses at targeting intracellular pathogens like viruses [5]. Antibodies can get distracted by viral particles and proteins, so they rely on the blind T-cell lymphocytes to ignore the surrounding virus particles and eliminate the infected host cell at the source. As naive T-cells circulate the lymph nodes and spleen, they express T-cell receptors (TCR) that recognize cell surface peptides (antigens) attached to major histocompatibility complex (MHC) molecules on the surface of a specific pathogen. These surface MHC proteins tell the T-cells where to attack [5]. The dendritic cells work to activate the adaptive immune response by ingesting viral proteins and turning them into cell surface peptides that bind to MHC molecules, forming peptide-MHC complexes. The TCR of naive T-cells recognize the peptide-MHC complexes and activate the T-cell. For T-cells to become active, they also need to bind to proteins from the dendritic cell via co-simulation. They then undergo clonal expansion and differentiate into effector T-cells [5]. Effector T-cells are also referred to as cytotoxic T lymphocytes (CTLs). They travel through the body to hunt down peptide-MHC presenting pathogens and kill the infected cells by releasing cytotoxic molecules [5].
The adaptive immune response is stimulated by the recognition of pathogen-associated molecular patterns (PAMPs). Within 1-2 weeks after infection, the B-cells produce antibodies while T-cells simultaneously increase proinflammatory cytotoxic molecules in a forceful attempt to eliminate the virus [7]. The uptick in Interleukin cytokines abbreviated as IL-1, IL-6, IL-8, and so on, flood the body with proinflammatory substances, which “chronically increase the stimulation of T-cells, resulting in a cytokine storm and T-cell exhaustion” [9]. T-cell exhaustion not only means that the virus is overwhelming the body’s antibodies but also draining the strength of the T-cell’s ability to eliminate the virus at the source of infected host cells. SARS-CoV-2 is a “high-grade chronic viral infection because it decreases the responsiveness of T-cells leading to a decreased effector function and lower proliferative capacity” [9]. T-cell exhaustion is also linked to an increase in inhibitory receptors that can initiate apoptosis in T-cells. This results in the destruction of T-cells and their co-receptors, further suppressing the T-cells, as well as B-cells and NK cells, all of which are white blood cells (lymphocytes). Thus, explaining the general lymphopenia (the lack of lymphocytes) observed in severe COVID-19 cases and the increased number of cytokines [9]. Viral entry and attachment to ACE2 receptors trigger a vicious cycle of both innate and adaptive immune responses, mounting an intense attack by secreting proinflammatory substances that invite more lymphocytes to try and kill the virus. This releases more cytokines and chemokines [11]. The downregulation of the ACE2 enzyme results in a cascade of chemical reactions that lead to further inflammation and destruction of cells, weakening and damaging the body’s own immune response.
pathologies of a pandemic:
COVID-19 Autopsies
Once the SARS-CoV-2 attaches to alveolar type II cells, it propagates within the cells. Most viral particles cause apoptosis, releasing more self-replicating pulmonary toxins. Figure 3 displays normal ACE2 receptors located in the type II pneumocytes. Healthy alveoli are unobstructed to allow efficient diffusion of oxygen and carbon dioxide with red blood cells.
Figure 3
Figure 3 – “Type I pneumocytes are very thin in order to mediate gas exchange with the bloodstream (via diffusion). Type II pneumocytes secrete a pulmonary surfactant in order to reduce the surface tension within the alveoli” [12].
In contrast to Figure 3, Figure 4 shows the histopathology of alveolar damage (A) and inflammation (B) of the epithelial cells. As the epithelial cells detach from the alveolar wall the alveoli structures collapse and no longer inflate making it hard for patients with severe cases of COVID to breathe [13]. This results in diffuse alveolar damage with fibrin rich hyaline membranes and hemorrhages in the lungs [13]. The histopathology also detected multinucleated cells that lead to pulmonary fibrosis (scarring in the lungs). Infected cells are “abnormally large and often polynucleated cells showing a large cytoplasm with intense staining for the COVID-19 RNA probe” [13]. The viral Spike protein is also largely detected in the histopathology of COVID cases (C). The nuclei of Spike-positive cells appear an intense red stain and have abnormally enlarged cytoplasts (panel h) [13].
Figure 4
Figure 4 – “Histopathological evidence of alveolar damage, inflammation and SARS-CoV-2 infection in COVID-19 lungs” [13].
The cellular destruction detected in the histopathology is macroscopically reflected in the physical damage of lung tissue displayed in Figure 5.
Figure 5
Figure 5 – “Macroscopic appearance of COVID lungs” [13].
In all pathological examinations of patients that died of COVID, their lungs sustained macroscopic damage [13]. Severe cases of COVID reveal congested and firm lungs (A) with “hemorrhagic areas and loss of air spaces (a’, c’)” [13]. As the virus ravages the body, some patients rapidly deteriorate and develop severe inflammation and clotting in the lungs (B) which shows “the thrombosis of large pulmonary vessels, often with multiple thrombi and in one case determining an extensive infarction in the right lobe (Fig. 5B panels a and b)” [13]. The lung’s architecture crumbles as cells lose their integrity and continue to die, thus resulting in the development of Acute Respiratory Distress (ARDS). ARDS develops in about 5% of COVID-19 patients, and of all the infected, the mortality rate remains around 1 to 2% [14]. Autopsies are beginning to reveal that rather than a singular cause of death, many factors seem to be responsible for higher mortality rates in patients that develop critical cases of COVID-19.
The fallout from the hyperactive immune response disrupts regular oxygen diffusion from the alveoli into the capillaries and consequently to the rest of the body. This commonly leaves fluid and dead cells, resulting in pneumonia, a condition in which patients experience symptoms such as coughing, fever, and rapid or shallow breathing [14]. If oxygen levels in the blood continue to drop, patients rely on breathing assistance by a ventilator to forcefully push oxygen into damaged lungs “riddled with white opacities where black space—air—should be” [14]. The presence of opacities in the lungs indicate the development of pneumonia into ARDS, which was found in the autopsy of a 77-year-old man with a history of comorbidities, including hypertension and the removal of his spleen (splenectomy) [15]. The decedent exhibited chills and an intermittent fever but no cough for 6 days. On March 20, 2020, emergency medical services responded to a call, stating that the deceased was experiencing weakness, fever, and shortness of breath. In route to the hospital, the decedent went into cardiac arrest and died shortly after reaching the hospital [15]. A postmortem nasopharyngeal swab was administered and came back positive for SARS-CoV-2.
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Figure 6 |
Figure 7 |
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| Figure 6 – Normal chest X-Ray of healthy lungs [16]. | Figure 7 – “Lesion segmentation results of three COVID-19 cases displayed using the software post-processing platform” [17]. |
Figure 7 shows opacities in the CT “of typical COVID-19 infection cases at three different infection stages: the early stage, progressive stage, and severe stage” [17]. Figure 7 highlights these opacities in red, which appear to intensify and cover more of the lung CT as the virus increases in severity (a-c). Patient 4 (c) exhibits what medical examiners refer to as a “complete whiteout” of the lungs. Indicating reduced air flow, whereas the normal scan of healthy lungs (Figure 6) has a black background, representing the transparency of free and unrestricted airflow.
The postmortem radiography of the deceased 77-year-old man showed “Diffuse, dense bilateral airspace consolidations (complete “whiteout”)” [15]. In most cases of severe COVID-19 “the greatest severity of CT findings is visible around day 10 after the symptom onset. Acute respiratory distress syndrome is the most common indication for transferring patients with COVID-19 to the ICU” [18].
ARDS in connection to SARS-CoV-2 was first documented in Wuhan, Hubei, China in December 2019 with over 90,000 deaths associated with organ dysfunction, particularly progressive respiratory failure and the formation of blood clots resulting in the highest mortality rates [19]. Another autopsy from Hamburg, Germany conducted on the first 12 documented consecutive cases of COVID-19 related deaths revealed that there was not only profuse alveolar damage in 8 out of the 12 patients but also a high rate of clotting resulting in death. 75% of patients that died were males within an age range of 52 to 87 years and 7 out of 12 patients autopsied (58%) presented venous thromboembolism, as displayed in Figure 7. A pulmonary embolism was the direct cause of death in 4 of the deceased [20].
Figure 8
Figure 8 – “Macroscopic autopsy findings: A. Patchy aspect of the lung surface (case 1). B. Cutting surface of the lung in case 4. C. Pulmonary embolism (case 3). D. Deep venous thrombosis (case 5)” [20].
The formation of clots results in pulmonary vasoconstriction, or the constriction of arteries and halting of blood delivery to the arteries and capillaries in the lungs. Blood cannot travel to the lungs, so oxygen levels drop. As a result, a cytokine storm from our hyperactive immune system occurs, destroying the alveolus and the endothelium and causing clots to form. Smaller clots come together and form a fatal giant blood clot, or the clots can break apart and travel to other parts of the body, causing a blockage and inadequate blood supply to organs or other parts of the body [19]. If the blood supply to fingers, toes, and other extremities is cut off by a clot, it is referred to as ischemia and often results in the amputation of digits and appendages once the flesh begins to die [19].
When SARS-CoV-2 enters the alveolar cells in the lungs via the ACE2 receptors, it can directly attack organs and indirectly cause damage to other organs by triggering a hyperactive immune response (cytokine storm). When the viral particles trigger a cytokine storm, they cause further inflammation of the lungs resulting in plummeting oxygen levels and the formation of blood clots in the arteries (arterial thrombosis).
Conclusion
SARS-CoV-2 is a multi-organ scourge, but it primarily attacks the lung by first attaching its spike protein to the host cell’s ACE2 receptors. This prevents the lungs from regulating their function because it inhibits ANG II protein breakdown, causing increased alveolar damage and inflammation of the lungs. The virion proteins create proinflammatory responses in the innate immune response and compromise an effective adaptive immune response. As the virus progresses the number of neutrophils from the innate immune response increase while the number of helpful lymphocytes (T-cells and B-cells) decrease. The ACE2 receptors overstimulate the innate and adaptive immune response to produce more proinflammatory molecules to eliminate the virus, thus causing more destruction to the body and its immune response. Autopsies of COVID-19 victims show ongoing cellular death and collapse of the respiratory system caused by inflammation and alveolar damage that eventually develop into ARDS. Extreme inflammation induced by the immune response causes difficulties in breathing and clotting in the lungs. Radiography of progressive stages of COVID identify opacities in lung CTs indicating obstructed airways and alveolar deterioration. Postmortem examinations reveal gross destruction of the lung tissue, such as pulmonary artery thrombosis, vasoconstriction, lung infarction, or pulmonary embolism. Progressive organ and respiratory failure and abnormal clotting are all contributing factors to the cause of death in the most severe cases of COVID-19.
SARS-CoV-2 efficiently exploits weaknesses not only within our innate and adaptive immune systems across sex, age, race, and ethnicity, but it also exploits weaknesses within our societies. The etymological origins of Pandemic are rooted in pandēmos , which is Greek for ‘all’ (pan)+ ‘people’ (demos). When simplified, pandemic literally means “all people” but the priorities of leadership across the world reveal that not all people suffer the burden of this pandemic equally. Regarding the United States’ approach to the pandemic, this quote from the Atlantic’s article “Why Some People Get Sicker Than Others” is sufficient; “the damage of disease and a global pandemic is not a mystery. Often, it’s a matter of what societies choose to tolerate. America has empty hotels while people sleep in parking lots. Food is destroyed every day while people go hungry. Americans are forced to endure the physiological stresses of financial catastrophe while corporations are bailed out. With the coronavirus, we do not have vulnerable populations so much as we have vulnerabilities as a population. Our immune system is not strong” [21].
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