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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:

  1. 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
  2. Bischel, Heather. Catching up with our public-facing COVID-19 wastewater research. Accessed August 15, 2021.Available from H.Bischel.faculty.ucdavis
  3. 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.
  4. Healthy Davis Together. Accessed  February 2, 2021. Available from Healthy Davis Together – Working to prevent COVID-19 in Davis
  5. UCMerced Researchers. Covid Poops Summary of Global SARS-CoV-2 Wastewater Monitoring Efforts. Accessed February 2, 2021. Available from COVIDPoops19 (arcgis.com) 
  6. Walter S Leal. January 13, 2021. COVID symposium Questions about Tests and Vaccines. Live stream online on zoom.

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. 

 

References:

  1. Joshi SC, Sheikh AA. 2015. 3D printing in aerospace and its long-term sustainability. Virtual Phy Prototy [Internet]. 10(4):175–185. doi.org/10.1080/17452759.2015.1111519
  2. Hodkinson PD, Anderton RA., Posselt BN, Fong KJ. 2017. An overview of space medicine. Br J Anaesth [Internet]. 119(suppl_1):i143–i153. doi.org/10.1093/bja/aex336
  3. Aglietti, GS. 2020. Current Challenges and Opportunities for Space Technologies. Front Space Tech [Internet]. 1:1. doi.org/10.3389/frspt.2020.00001
  4. Coopersmith J. 2011. The cost of reaching orbit: Ground-based launch systems. Space Policy  [Internet]. 27(2):77–80. doi.org/10.1016/j.spacepol.2011.03.001
  5. Ghidini T. 2018. Regenerative medicine and 3D bioprinting for human space exploration and planet colonisation. J Thorac Dis [Internet]. 10(Suppl 20):S2363–S2375. doi.org/10.21037/jtd.2018.03.19
  6. Gleaton J, Lai Z, Xiao R, Chen Q, Zheng Y. 2019. Microalga-induced biocementation of martian regolith simulant: Effects of biogrouting methods and calcium sources. Constr Build Mater [Internet]. 229:116885. doi.org/10.1016/j.conbuildmat.2019.116885
  7. Pilehvar S, Arnho M, Pamies R, Valentini L, Kjøniksen AL. 2020. Utilization of urea as an accessible superplasticizer on the moon for lunar geopolymer mixtures. J Clean Prod [Internet]. 247:119177. doi.org/10.1016/j.jclepro.2019.119177
  8. Kumar A, Dikshit R, Gupta N, Jain A, Dey A, Nandi A., … Rajendra A. 2020. Bacterial Growth Induced Biocementation Technology, ‘Space-Brick’ – A Proposal for Experiment at Microgravity and Planetary Environments. BioRxiv  [Internet]. 2020.01.22.914853. doi.org/10.1101/2020.01.22.914853
  9. Lopez JV, Peixoto RS, Rosado AS. 2019. Inevitable future: space colonization beyond Earth with microbes first. FEMS Microbiol Ecology [Internet]. 95(10). doi.org/10.1093/femsec/fiz127
  10. Bornemann G, Waßer K, Tonat T, Moeller R, Bohmeier M, Hauslage J. 2015. Natural microbial populations in a water-based biowaste management system for space life support. Life Sci Space Res [Internet]. 7:39–52. doi.org/10.1016/j.lssr.2015.09.002
  11. Bokulich NA, Lewis ZT., Boundy-Mills K, Mills DA. 2016. A new perspective on microbial landscapes within food production. Curr Opin Biotechnol [Internet]. 37:182–189. doi.org/10.1016/j.copbio.2015.12.008
  12. 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
  13.  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
  14. 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
  15. 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
  16. 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
  17. Ellman GL, Courtney KD, Andres VJ, Feather-Stone RM. 1961. A new and rapid colorimetric determination of acetylcholinesterase activity. Biochem Pharmacol [Internet]. 7:88–95. doi.org/10.1016/0006-2952(61)90145-9
  18. Alkanaimsh S, Karuppanan K, Guerrero A, Tu AM, Hashimoto B, Hwang MS, … McDonald KA. 2016. Transient Expression of Tetrameric Recombinant Human Butyrylcholinesterase in Nicotiana benthamiana. Front Plant Sci [Internet]. 7:743. doi.org/10.3389/fpls.2016.00743
  19. Gu Z, Fu K, Lin H, He Y. 2020. Development of 3D bioprinting: From printing methods to biomedical applications. Asian J Pharm Sci [Internet]. 15(5):529–557. doi.org/10.1016/j.ajps.2019.11.003
  20. Ngamelue MN, Homma K, Lockridge O, Asojo OA. 2007. Crystallization and X-ray structure of full-length recombinant human butyrylcholinesterase. Acta Crystallogr [Internet]. 63(9):723-727. doi.org/10.1107/S1744309107037335
  21. Macharoen K, McDonald KA, Nandi S. 2020. Simplified bioreactor processes for recombinant butyrylcholinesterase production in transgenic rice cell suspension cultures. Biochem Eng J [Internet]. 163:107751. doi.org/10.1016/j.bej.2020.107751

Reproductive and Developmental Health Effects of PFAS on Animal Models: A Review of Current Literature

By Anna Maddison, Environmental Toxicology ‘21, Janaé Bonnell, Environmental Toxicology ‘22, Dr. Michele La Merrill

Authors’ Note: This literature review was conducted for the Office of Environmental Health Hazard Assessment in the California Environmental Protection Agency under a contract issued to Dr. Michele La Merrill. We wanted to understand the current research on the reproductive and developmental toxicity of PFHxS, PFBS, PFHxA, PFHpA, PFNA, PFDA, and ADONA to draw conclusions and make recommendations for future policy and research. It is important to understand the health effects of substances such as PFAS chemicals that are present in our food, water, and consumer products to develop regulatory standards that protect public health.

 

Abstract

Per- and polyfluoroalkyl (PFAS) chemicals are used in the production of many industrial processes and consumer goods, and they have been widely detected in humans and animals. PFOS and PFOA have been comprehensively studied and are being phased out of use, but there are other understudied PFAS chemicals with effects that should be considered in regulatory affairs regarding public health and safety. In this study, we focus on the reproductive and developmental effects of seven PFAS chemicals: perfluorononanoic acid (PFNA), perfluorohexanoic acid (PFHxA), perfluorohexane sulfonic acid (PFHxS), 4,8-dioxia-3H-perfluorononanoic acid (ADONA), perfluorobutane sulfonic acid (PFBS), perfluoroheptanoic acid (PFHpA), perfluorodecanoic acid (PFDA). This literature review presents the observed reproductive and developmental effects of these chemicals on animal models, which can be used to help establish legislative priorities and draw attention to current gaps in published literature.

Keywords: PFAS, review, animal model, PFBS, PFHxS, PFHpA, PFHxA, PFDA, PFNA, ADONA

 

Introduction

Poly- and perfluoroalkyl (PFAS) chemicals are widespread synthetic chemicals that are highly mobile, persistent in the environment, and are known to bioaccumulate in humans and animals[1,2]. PFAS chemicals have extensive use due to their unique anti-wetting abilities, as well as their ability to act as a surfactant, a molecule that lowers the surface tension between two liquids[3]. These properties have led to their use in oil- and water-repellent textiles, coatings, and fire-retardant products. PFAS chemicals can also be found in drinking water, production facilities and industries, and many commercial household products[1,4]. Humans are mainly exposed to PFAS through their diet but are unable to metabolize these chemicals in their bodies[5,6]

These chemicals have found use in multiple industries for over 60 years[7]. PFAS production peaked in the 1990s, with PFOS and PFOA being the most popularly used PFAS chemicals. However, after studies linked these chemicals to adverse human health effects, including damage to the immune system and liver, reproductive and developmental harm, hormone disruption, and cancer, the United States had voluntarily phased out their use[1,5,2]. The industry has since shifted to favor PFASs with shorter chains, as these were believed to be less harmful to human health[7,8]. Although no association between chain length and toxicity has been proven, it is still being explored. 

To this end, perfluorohexane sulfonic acid (PFHxS), perfluorobutane sulfonic acid (PFBS), perfluorohexanoic acid (PFHxA), perfluoroheptanoic acid (PFHpA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and 4,8-dioxia-3H- perfluorononanoic acid (ADONA) have been increasingly used for industrial purposes as alternatives to PFOS and PFOA[6,8]. These PFAS chemicals have shorter carbon backbone chains, so it is believed they may have less negative health effects than PFOA and PFOS, but this has not been proven. However, their health effects are not as well-explored as those of PFOS and PFOA, thus necessitating new research into the long-term health impacts of exposure to these replacement PFAS chemicals.

Multiple epidemiological studies in humans have suggested that there is an association between PFAS exposure and adverse reproductive and developmental health impacts. After exposure during pregnancy, lower levels of thyroid hormones T3 and thyroxine have been observed in both pregnant women and fetuses, as well as adverse birth outcomes and behavioral effects on children exposed in-utero[6,9]. Some of these PFAS chemicals, such as PFNA, are being detected in both seminal plasma and breast milk of humans[10].

Individuals who are not fully developed may be more vulnerable to PFAS exposure and therefore, more at risk for any toxic effects. The purpose of this literature review is to survey reproductive and developmental effects of PFAS exposure to inform on potential literary gaps and future regulatory priorities. 

 

Methods

Search Procedure

The research for this literature review was conducted by systematically choosing articles discovered through the search engine PubMed. The initial database of articles was created from searching the abbreviated forms of the chemical names (PFHxS, PFBS, PFHxA, PFHpA, PFNA, PFDA, ADONA) in PubMed using the filter “Other Animals” (Table 1). Only papers in English were considered for inclusion. An exception was made for ADONA due to our search yielding an excess of papers written by an author by that name. Instead the search term “ADONA NOT adona [author]” was used. Even with the reduced search, many of the results did not include the PFAS chemical ADONA, and subsequently, were not included. 

 

Table 1: Contains a list of searches and number of results yielded for each one.

Search Date Search Term(s) Number of Results
April 15th, 2020 PFHxS 124
April 25th, 2020 PFBS 78
April 25th, 2020 PFHxA 54
April 25th, 2020 PFHpA 29
April 25th, 2020 PFNA 189
April 25th, 2020 PFDA 198
April 26th, 2020 PFHxS 125
May 12th, 2020 PFHpA 30
May 13th, 2020 PFDA 199
May 15th, 2020 “ADONA NOT adona [author]” 14
May 29th, 2020 PFDA 200

 

Study Selection

The titles and abstracts of each article were scanned for relevance to reproductive toxicity. This includes in vitro studies on isolated cells, different toxicological effects based on sex, responses affecting reproductive organs, and developmental effects in offspring. To limit the scope, this excluded human studies, bioconcentration studies that did not specify reproductive organs or unique developmental patterns, wildlife studies, and studies focused on other organ systems not in the context of reproduction or development. Additionally, we chose to exclude studies which used a mixture of chemicals or in which the PFAS chemical was analyzed as a metabolite of a parent chemical. This was due to the fact that it is uncertain which chemical actually caused an effect. Relevant articles were examined in depth to determine significant toxicological effects of the PFAS chemicals. The number of relevant articles in comparison to the total articles which arose from our search can be seen in Table 2. Other notable responses, from papers which included reproductive effects, were denoted in our accompanying spreadsheet. Due to time constraints, the results for PFDA were summarized with less depth and were instead included as an appendix. 

 

Table 2: Contains the number of resulting studies chosen for inclusion in this review.

Chemical Articles Used in Our Research
Perfluorononanoic Acid PFNA 17
Perfluorohexanoic Acid PFHxA 5
Perfluorohexane Sulfonic Acid PFHxS 11
4,8-3H-Perfluorononanoic Acid ADONA 1
Perfluorobutane Sulfonic Acid PFBS 15
Perfluoroheptanoic Acid PFHpA 2
Perfluorodecanoic Acid PFDA 16

 

Results

PFNA

Seventeen studies contained relevant reproductive and/or developmental effects of PFNA exposure. All of these studies except for one, which dosed Xenopus laevis (African clawed toad, African claw-toed frog or the platanna), examined the effects of PFNA exposure on Danio rerio (zebrafish), Rattus (rats), or Mus (mice). These studies are compiled in Supplementary Table 1 (ST1).

PFNA exposure in Danio rerio caused embryo disfigurement and altered motion patterns, as well as other reproductive and developmental effects. In recently fertilized eggs, PFNA exposure resulted in an increase in malformation rate[6], specifically, in the rate of ventricular edema[19]. Studies also showed correlation between PFNA exposure and locomotion: Danio rerio exposed as embryos travelled less distance [11][13][6], their activity level increased[24] [13], they bumped into the mirror more[13], their startle response and burst activity increased[6],  the amount of time they spent in the middle of the water, and their velocity changed[13][11]. Additionally, exposure to PFNA caused reproductive effects such as an increase in the number of opaque embryos[19][, a decrease in hatching rate[19][15], a decrease in the number of eggs in females[15], and an increase in yolk sac area[11]. Observed developmental effects included a decrease in body length[13], abnormally enlarged follicles in the thyroid, and increased T3 hormone levels[18]

In Mus and Rattus, the most observed reproductive effects occurred in the testis. In Rattus, cell viability in Sertoli[12] and testicular[23] cells decreased, DNA damage in testicular cells increased[23], vacuoles formed in the Sertoli cells[12], the number of germ cells that degenerated or were TUNEL-positive increased[12][20], and the percentage of apoptotic cells in the testis increased[20]. In Mus, intratesticular and serum levels of testosterone, testicular glucose level, and testicular lactate concentration decreased[14][10]. Also in Mus, seminiferous tubules had intraepithelial vacuolation where small cavities formed in the tubules, marginal condensation of chromatin in round spermatids, and giant cells and exfoliation of germ cells in the lumen of the tubules[14]. Reproductive effects in mammals exposed to PFNA included reduced prenatal and postnatal survival[16], maternal weight decreased[16][25], and lower birth weight and higher blood pressure in pups[25]. Additionally, there was a sex-specific difference in that serum concentration of PFNA decreased more rapidly in adult females than males[17]. Finally, the developmental effects of PFNA exposure in Mus who had not experienced puberty included a decrease in weight, an increase in absolute and relative liver weight, and hepatocellular hypertrophy[14][10].

In Xenopus laevis, PFNA exposure resulted in increased embryo mortality and malformations including stunted tadpole length, multiple edemas, gut miscoiling, microcephaly in which the offspring had abnormally small heads, and skeletal kinking[22].

PFHxA

Five articles on reproductive and/or developmental effects of PFHxA, which showed statistically significant responses, were found to be relevant to our study. These studies are compiled in Supplementary Table 2 (ST2).  Each of the five papers studied a different animal: Danio rerio, Daphnia magna, anuran Xenopus laevis, Mus, and Brachionus calyciflorus. In both Danio rerio and anuran Xenopus laevis embryos, a decrease in body length was observed in the animals exposed to PFHxA[26][28]. In Daphnia magna, reproductive output increased with chronic exposure to PFHxA and mobility decreased with acute exposure to PFHxA[27]. In the Mus, indirect exposure in utero to PFHxA resulted in pups taking longer to open their eyes, a decrease in their body weight, and a lower ratio of liver to body weight[29]. Xenopus also saw liver effects in the form of swollen livers in tadpoles[28. In Brachionus calyciflorus, the rate of population increase decreased, and the mictic ratio, the ratio between eggs that require fertilization and those that do not, and egg size increased[30].

PFHxS

Using the methods described above, fifteen articles examining the effects of PFHxS on Mus, Rattus, Gallus gallus domesticus, and Danio rerio were within the scope of our literature review. These studies are compiled in Supplementary Table 3 (ST3). In the mammals, notable, visible reproductive and developmental effects were observed. In general, male mammals dosed with PFHxS seemed to present more deviations from the control opposed to females. For example, when PFHxS was orally administered or injected via IV, male Rattus took a significantly longer time to expel it from their plasma than female Rattus[38]. Other instances of this trend were apparent when male pups displayed increased anogenital distance[35] and decreased weight gain[36] at more concentrations than females. Other effects of PFHxS in mammals included decreased activity[32] and increased liver and thyroid weight[35] in pups who were respectively dosed neonatally and exposed indirectly in utero as well as directly for two weeks. In Gallus gallus domesticus, PFHxS egg injections decreased pipping success, which is the chick’s ability to break themselves out from their shell, and decreased the mass of embryos[37]. Finally, in Danio rerio embryos an EC50 value was calculated to be 84.5μM using the concentration at which they died or suffered from an adverse effect, defined to be non-inflated swim bladder, pericardial or yolk sac edemas, or scoliosis, as a reference[34]. Altered motion patterns and body lengths were also observed[6][26]. 

ADONA

Only one article was found that showed reproductive effects of ADONA. This study is shown in Supplementary Table 4 (ST4). Pregnant Rattus norvegicus were exposed to ADONA via oral administration which resulted in a decrease in pup weight, maternal food consumption while pregnant, maternal weight gain, and the number of pups that survived[40]. A higher dosage was abandoned after two days due to death, significant body weight loss, reduced food consumption, decreased activity, dehydration, coldness to touch, pale extremities, rales or rattling sounds in the lungs, ungroomed coat, urine-stained fur, and ptosis or drooping eyelids in the pregnant Rattus[40].

PFBS

Seventy-nine articles resulted from a PubMed search on perfluorobutane sulfonic acid (PFBS) using the above-described methods. Of those seventy-nine articles, fifteen were deemed to be within the scope of this review. These studies are compiled in Supplementary Table 5 (ST5). These studies investigated the effects of PFBS on Mus musculus (mice), Oryzias melastigma (marine medaka), Caenorhabditis elegans, Danio rerio, Rattus norvegicus (rats), Xenopus laevis, and C. riparius (harlequin flies). A multitude of adverse reproductive effects was observed as a result of PFBS exposure. Multiple studies demonstrated that PFBS affects hormone levels in both ICR Mus and Oryzias, generally including a decrease in estrogen levels in all animals and a testosterone decrease in males[7][43]. One study noted that males were experiencing estrogenic changes and females were experiencing antiestrogenic changes as a result of PFBS exposure[43]. PFBS exposure also leads to alterations in levels of follicle-stimulating hormone and progesterone[7][43]. In several egg-producing organisms studied, it was found that overall egg production was significantly decreased[42][43] and that this effect could also occur after several generations of exposure to PFBS[48]. In both Mus and Oryzias, significant decreases in uterus and ovary size were recorded in both exposed organisms[43][9]. These species also had significant changes in the number of follicles and oocytes in various stages after exposure[7][43][9]. Lastly, organisms were observed to have decreased length after exposure to PFBS, an effect that was usually more prominent in males[3][48][49]

First-generation offspring from exposed parents were observed to have changes in hormone levels that would affect growth and development, generally including increases in luteinizing hormone[43][9] and significant alterations in T3 concentration[3][9]. Reduced estrogen levels and elevation of thyroid-stimulating hormone were also observed[9]. The length of diestrus in Mus and Rattus was also significantly increased after parental exposure to PFBS[9][8]. Significant decreases in uterus and ovary size were recorded in the offspring of exposed Mus and Oryzias[43][9]. Mus offspring were also observed to have significant changes in the number of follicles and oocytes in various stages[9]. Furthermore, organismal body weight was observed to be influenced by parental PFBS exposure, although it both increased and decreased in separate experiments[3][8][48]. A study exploring the influence of maternal and paternal dosage on Oryzias offspring observed greater negative impacts on offspring related to paternal exposure to PFBS rather than maternal exposure, such as swimming hyperactivity[44]. Offspring of exposed parents also experienced deformities, such as increased tail and craniofacial malformations in Danio rerio[49]. Lastly, it was observed that PFBS exposure delayed both the age of vaginal opening[9] and preputial separation in Mus and Rattus with parents exposed to PFBS[8].

Of the fifteen studies included, only two focused on the multigenerational effects of PFBS on organismal reproduction and development. PFBS was observed to affect T4 hormone concentration in F2 generation Oryzias after a life-cycle exposure during the F0 generation[3]. In the same species, both the weight of F2 generation eggs, as well as their lipid and protein content, were significantly increased after ancestral exposure during the F0 generation development[43]

PFHpA

A search of PubMed using the above methods yielded thirty results for the chemical PFHpA. Of these thirty results, two were found to be within the scope of this review. These studies are compiled in Supplementary Table 6 (ST6). These reports studied the effects of multiple chemicals, including PFHpA, on Danio rerio and Xenopus laevis via exposure in solution.  Both studies are described here due to the limited number of papers. The lowest-observed-adverse-effect levels in the Menger[6] and Kim[28] studies were found to be 89 µM and <0.25 mM (250 μM) renewed daily, respectively. The findings in these studies suggest that PFHpA is both a possible teratogen negatively affecting the embryo or fetus and a developmental toxicant in multiple animal species[28]. A dose-response relationship was exhibited regarding PFHpA dosage and rates of both malformations and mortality in Xenopus embryos[28]. Observed malformations included reduction of body length in 24% of Xenopus tadpoles dosed with 1,000 µM of PFHpA as embryos, as well as enlarged, abnormal livers[28]. However, the observation of reduced tadpole body length was only noted at a dosage of 1,000 µM of PFHpA, which is comparable to the LC50 value in this study, found to be 942.4 µM[28]. There was also evidence of potential behavioral effects in developing organisms. For example, Danio rerio exposed to PFHpA had a significant decrease in swimming distance recorded at the highest dosage[6]. No studies listed in PFHpA searches investigated the reproductive hazard of the chemical.

PFDA

Of the two hundred articles listed for PFDA on PubMed using the above search methods, sixteen studies were considered relevant to be included within this report. These sixteen studies are summarized in Appendix 1 (A1) and a subset of them is highlighted here. Both the viability and maturation of pig oocytes was shown to be negatively impacted by exposure to PFDA[50]. The thyroid was shown to be affected in multiple studies, with thyroid hormone levels being both decreased[59][61][62]  and increased[57] in different reports. PFDA also adversely affected the sexual organs of exposed organisms, including the seminal vesicle[56] and seminiferous tubules[60]. In rats, hamsters, and guinea pigs, degeneration of the seminiferous tubules was observed following PFDA exposure[60].

Outside of the 184 remaining studies not included in Appendix 1, three studies stated that PFDA may be estrogen-like in its action. However, these three papers did not contain health endpoints that were within the scope of this report, such as gene expression and carcinogenesis[64][65][66]. These papers are referenced within the sources of this report but were not included within the review of reproductive and developmental health, nor were they included within Appendix 1 (A1). 

 

Discussion

While the toxicity of PFBS, PFHxS, PFHpA, PFHxA, PFDA, PFNA, and ADONA, which are used as substitutes for PFOS and PFOA, is still being investigated, the current body of scientific research suggests that exposure to these PFAS chemicals poses potential reproductive and developmental risk to an organism.

In several species, PFNA exposure resulted in several effects that could interfere with normal procreation and aging systems. Observed deviations from control groups included embryo malformation, offspring mortality, altered behavioral patterns, morphological abnormalities, weight changes, and different hormone levels. There was evidence to suggest that males retain more PFNA than their female counterparts, and several studies suggested that male sex organs were impacted by PFNA exposure. Relative to the other PFAS chemicals studied in this paper, PFNA had a high amount of significant papers with reproductive and developmental effects. This may suggest that it poses a higher risk than some of the other chemicals, but it should be considered in the context that PFNA also had a higher number of search results than the other chemicals and therefore, may just be more well studied. A limitation in these findings that should be considered is the apparent lack of corresponding research on female sexual organs. Also, several effects were not observed to have a dose-dependent response, while others were only seen at lower concentrations. 

PFHxA only had five relevant studies and each used a different species as test subjects. Additionally, there were four studies, two used in the results of PFHxA and two not used due to a lack of significant results, which also did their experiments with other PFAS chemicals, and in comparison, individuals dosed with PFHxA had milder, if any, effects. This suggests that PFHxA may have lower reproductive and developmental toxicity than other PFAS chemicals in this paper. This could be taken into consideration when assessing the risk of exposure associated with this chemical. 

PFHxS, similar to PFNA, had more toxic effects in males than females. Unlike the studies using PFNA, a majority of these did test both males and females in the same conditions. Exposed males retained a higher serum concentration of PFHxS for longer and displayed changes in anogenital distance and weight at a larger range of dosage concentrations than females.

There was one relevant paper that addressed the reproductive and developmental effects of ADONA exposure. This, coupled with the potential conflict of interest presented by the funding,  makes it impossible to draw any conclusions regarding the toxicity of this chemical. Even so, effects were observed from exposure to ADONA. These included changes in weight, mortality rate, and food consumption. To further understand the reproductive and developmental toxicity of ADONA, further research is necessary. 

Multiple species demonstrated adverse reproductive and developmental health outcomes after exposure to PFBS. Alterations to hormone levels and morphological abnormalities were observed following PFBS dosage. Also, PFBS was seen to potentially influence hormonal sex changes in exposed fish. Several studies emphasized the impacts PFBS exposure may have on offspring. The above changes were seen in offspring after parental exposure, as well as alterations to egg development and the size of female reproductive organs. It was also noted that paternal exposure to PFBS tends to more negatively impact the health of offspring than maternal exposure does. Compared to other chemicals included  within this report, PFBS had a relatively high number of studies that met the requirements for inclusion. 

Only two relevant studies were found regarding PFHpA, each using a different test species. These studies investigated the developmental effects of PFHpA on organisms exposed as embryos or tadpoles. Findings suggested that PFHpA may be teratogenic and toxic to developing organisms based on resulting morphological abnormalities and behavioral alterations in exposed organisms. However, no studies were found to investigate the reproductive impacts of PFHpA exposure, leading to a gap in the available research on this chemical.

The studies included on PFDA cover its effect on cell viability, hormone levels, and sex organs, as well the potential developmental toxicity and teratogenicity of PFDA exposure. However, within these studies, there are limitations. Multiple studies did not include information on the age at which organisms, usually Rattus, were dosed, making it more difficult to fully comprehend the effects of PFDA on stages of animal growth. Compared to several of the chemicals included in this paper, PFDA has a relatively higher number of papers that met the criteria for inclusion. Studies have been conducted on this chemical since the 1980s, far preceding work on some of the other chemicals in this report. Furthermore, while the effects of PFDA on hormones and the thyroid have been investigated in several studies, little work appears to have been done on the multigenerational and offspring effects of PFDA. Lastly, five of the sixteen studies investigated the effects of PFDA only on males, leaving further information on female-specific effects to be desired. Both multigenerational and female-specific studies could be considered potential avenues for further research.

Overall, these PFAS chemicals have demonstrated that they may have potential for reproductive and developmental health effects, and their effects on humans should be investigated to ascertain human risk. 

 

Conclusion

The objective of the present study was to compile and summarize the toxic effects of different PFAS chemicals on the reproduction and development of animals in controlled settings. While there are variations in the species used, as well as the method in which they were exposed and the concentration tested, exposure to all seven PFAS chemicals impacted aspects of development, and six had effects on reproduction. These effects should be considered in designing additional research on the outcomes of PFAS exposure and in assessing the risk of these chemicals on living organisms.

 

Acknowledgements

This work was conducted under California Environmental Protection Agency, Office of Environmental Health Hazard Assessment contract 17-E0024. The authors appreciate the support of Dr. David Furlow, professor of Neurobiology, Physiology, and Behavior and University Honors Program Director at University of California, Davis, and Dr. Sarah Elmore at the Office of Environmental Health Hazard Assessment. 

 

Abbreviations

DPF days post-fertilization
E2 estrogen/estradiol
FSH follicle stimulating hormone
GD gestation day
GnRH Gonadotropin-releasing hormone
HPF hours post-fertilization
KT-11 11-keto-testosterone
LH luteinizing hormone
P4 progesterone
PFAA perfluoroalkyl acids
PND postnatal day
PPD postpartum day
T testosterone
T3 3,3’,5-triiodothyronine
T4 thyroxine
TBG thyroxine-binding globulin
TSH thyroid-stimulating hormone

 

References

  1. US EPA, O. (2016, March 30). Basic information on pfas [Overviews and Factsheets]. US EPA. https://www.epa.gov/pfas/basic-information-pfas
  2. Pelch, K. E., Reade, A., Wolffe, T. A. M., & Kwiatkowski, C. F. (2019). PFAS health effects database: Protocol for a systematic evidence map. Environment International, 130, 104851. https://doi.org/10.1016/j.envint.2019.05.045
  3. Chen, L., Hu, C., Tsui, M. M. P., Wan, T., Peterson, D. R., Shi, Q., Lam, P. K. S., Au, D. W. T., Lam, J. C. W., & Zhou, B. (2018). Multigenerational Disruption of the Thyroid Endocrine System in Marine Medaka after a Life-Cycle Exposure to Perfluorobutanesulfonate. Environmental Science and Technology, 52(7), 4432–4439. https://doi.org/10.1021/acs.est.8b00700
  4. Lau, C. (2015). Perfluorinated compounds: An overview. In J. C. DeWitt (Ed.), Toxicological Effects of Perfluoroalkyl and Polyfluoroalkyl Substances (pp. 1–21). Springer International Publishing. https://doi.org/10.1007/978-3-319-15518-0_1
  5. Kingsley, S. L., Eliot, M. N., Kelsey, K. T., Calafat, A. M., Ehrlich, S., Lanphear, B. P., Chen, A., & Braun, J. M. (2018). Variability and predictors of serum perfluoroalkyl substance concentrations during pregnancy and early childhood. Environmental Research, 165, 247–257. https://doi.org/10.1016/j.envres.2018.04.033
  6. Menger, F., Pohl, J., Ahrens, L., Carlsson, G., & Örn, S. (2020). Behavioural effects and bioconcentration of per- and polyfluoroalkyl substances (PFASs) in zebrafish (Danio rerio) embryos. Chemosphere, 245, 125573. https://doi.org/10.1016/j.chemosphere.2019.125573
  7. Cao, X. Yuan, Liu, J., Zhang, Y. Jie, Wang, Y., Xiong, J. Wei, Wu, J., & Chen, L. (2020). Exposure of adult mice to perfluorobutanesulfonate impacts ovarian functions through hypothyroxinemia leading to down-regulation of Akt-mTOR signaling. Chemosphere, 244, 125497. https://doi.org/10.1016/j.chemosphere.2019.125497
  8. Lieder, P. H., York, R. G., Hakes, D. C., Chang, S. C., & Butenhoff, J. L. (2009). A two-generation oral gavage reproduction study with potassium perfluorobutanesulfonate (K+PFBS) in Sprague Dawley rats. Toxicology, 259(1–2), 33–45. https://doi.org/10.1016/j.tox.2009.01.027
  9. Feng, X., Cao, X., Zhao, S., Wang, X., Hua, X., Chen, L., & Chen, L. (2017). Exposure of pregnant mice to perfluorobutanesulfonate causes hypothyroxinemia and developmental abnormalities in female offspring. Toxicological Sciences, 155(2), 409–419. https://doi.org/10.1093/toxsci/kfw219
  10. Singh, S., & Singh, S. K. (2019b). Acute exposure to perfluorononanoic acid in prepubertal mice: Effect on germ cell dynamics and an insight into the possible mechanisms of its inhibitory action on testicular functions. Ecotoxicology and Environmental Safety, 183, 109499. https://doi.org/10.1016/j.ecoenv.2019.109499
  11. Jantzen, C. E., Annunziato, K. A., Bugel, S. M., & Cooper, K. R. (2016). PFOS, PFNA, and PFOA sub- lethal exposure to embryonic zebrafish have different toxicity profiles in terms of morphometrics, behavior and gene expression. Aquatic Toxicology, 175, 160–170. https://doi.org/10.1016/j.aquatox.2016.03.026
  12. Feng, Y., Fang, X., Shi, Z., Xu, M., & Dai, J. (2010). Effects of PFNA exposure on expression of junction-associated molecules and secretory function in rat Sertoli cells. Reproductive Toxicology, 30(3), 429–437. https://doi.org/10.1016/j.reprotox.2010.05.010
  13. Jantzen, C. E., Annunziato, K. M., & Cooper, K. R. (2016). Behavioral, morphometric, and gene expression effects in adult zebrafish (Danio rerio) embryonically exposed to PFOA, PFOS, and PFNA. Aquatic Toxicology, 180, 123–130. https://doi.org/10.1016/j.aquatox.2016.09.011
  14. Singh, S., & Singh, S. K. (2019a). Prepubertal exposure to perfluorononanoic acid interferes with spermatogenesis and steroidogenesis in male mice. Ecotoxicology and Environmental Safety, 170, 590–599. https://doi.org/10.1016/j.ecoenv.2018.12.034
  15. Zhang, Sheng, Wang, Zhang, Dai. “Zebrafish Reproductive Toxicity Induced by Chronic Perfluorononanoate Exposure.” Aquatic Toxicology, June 2016, www.sciencedirect.com/science/article/pii/S0166445X16300959?via=ihub
  16. Das, K. P., Grey, B. E., Rosen, M. B., Wood, C. R., Tatum-Gibbs, K. R., Zehr, R. D., Strynar, M. J., Lindstrom, A. B., & Lau, C. (2015). Developmental toxicity of perfluorononanoic acid in mice. Reproductive Toxicology, 51, 133–144. https://doi.org/10.1016/j.reprotox.2014.12.012
  17. Tatum-Gibbs, K., Wambaugh, J. F., Das, K. P., Zehr, R. D., Strynar, M. J., Lindstrom, A. B., Delinsky, A., & Lau, C. (2011). Comparative pharmacokinetics of perfluorononanoic acid in rat and mouse. Toxicology, 281(1), 48–55. https://doi.org/10.1016/j.tox.2011.01.003
  18. Liu, Y., Wang, J., Fang, X., Zhang, H., & Dai, J. (2011). The thyroid-disrupting effects of long-term perfluorononanoate exposure on zebrafish (Danio rerio). Ecotoxicology, 20(1), 47–55. https://doi.org/10.1007/s10646-010-0555-3
  19. Liu, H., Sheng, N., Zhang, W., & Dai, J. (2015). Toxic effects of perfluorononanoic acid on the development of Zebrafish (Danio rerio) embryos. Journal of Environmental Sciences, 32, 26–34. https://doi.org/10.1016/j.jes.2014.11.008
  20. Feng, Y., Shi, Z., Fang, X., Xu, M., & Dai, J. (2009). Perfluorononanoic acid induces apoptosis involving the Fas death receptor signaling pathway in rat testis. Toxicology Letters, 190(2), 224–230. https://doi.org/10.1016/j.toxlet.2009.07.020
  21. Zheng, X.-M., Liu, H.-L., Shi, W., Wei, S., Giesy, J. P., & Yu, H.-X. (2012). Effects of perfluorinated compounds on development of zebrafish embryos. Environmental Science and Pollution Research, 19(7), 2498–2505. https://doi.org/10.1007/s11356-012-0977-y
  22. Kim, M., Son, J., Park, M. S., Ji, Y., Chae, S., Jun, C., Bae, J.-S., Kwon, T. K., Choo, Y.-S., Yoon, H., Yoon, D., Ryoo, J., Kim, S.-H., Park, M.-J., & Lee, H.-S. (2013). In vivo evaluation and comparison of developmental toxicity and teratogenicity of perfluoroalkyl compounds using Xenopus embryos. Chemosphere, 93(6), 1153–1160. https://doi.org/10.1016/j.chemosphere.2013.06.053
  23. Lindeman, B., Maass, C., Duale, N., Gützkow, K. B., Brunborg, G., & Andreassen, Å. (2012). Effects of per- and polyfluorinated compounds on adult rat testicular cells following in vitro exposure. Reproductive Toxicology, 33(4), 531–537. https://doi.org/10.1016/j.reprotox.2011.04.001
  24. Ulhaq, M., Örn, S., Carlsson, G., Morrison, D. A., & Norrgren, L. (2013). Locomotor behavior in zebrafish (Danio rerio) larvae exposed to perfluoroalkyl acids. Aquatic Toxicology, 144–145, 332–340. https://doi.org/10.1016/j.aquatox.2013.10.021
  25. Rogers et al. “Elevated Blood Pressure in Offspring of Rats Exposed to Diverse Chemicals During Pregnancy.” Toxicological Sciences, Society of Toxicology, Nov. 2013, academic.oup.com/toxsci/article/137/2/436/1675113
  26. Annunziato, K. M., Jantzen, C. E., Gronske, M. C., & Cooper, K. R. (2019). Subtle morphometric, behavioral and gene expression effects in larval zebrafish exposed to pfhxa, pfhxs and 6:2 ftoh. Aquatic Toxicology (Amsterdam, Netherlands), 208, 126–137. https://doi.org/10.1016/j.aquatox.2019.01.009
  27. Barmentlo, S. H., Stel, J. M., van Doorn, M., Eschauzier, C., de Voogt, P., & Kraak, M. H. S. (2015). Acute and chronic toxicity of short chained perfluoroalkyl substances to Daphnia magna. Environmental Pollution, 198, 47–53. https://doi.org/10.1016/j.envpol.2014.12.025.
  28. Kim, M., Park, M. S., Son, J., Park, I., Lee, H.-K., Kim, C., Min, B.-H., Ryoo, J., Choi, K. S., Lee, D.-S., & Lee, H.-S. (2015). Perfluoroheptanoic acid affects amphibian embryogenesis by inducing the phosphorylation of ERK and JNK. International Journal of Molecular Medicine, 36(6), 1693–1700. https://doi.org/10.3892/ijmm.2015.2370
  29. Iwai, H., & Hoberman, A. M. (2014). Oral (Gavage) combined developmental and perinatal/postnatal reproduction toxicity study of ammonium salt of perfluorinated hexanoic acid in mice. International Journal of Toxicology, 33(3), 219–237. https://doi.org/10.1177/1091581814529449
  30. Iwai, H., Hoberman, A. M., Goodrum, P. E., Mendelsohn, E., & Anderson, J. K. (2019). Addendum to Iwai and Hoberman (2014)—Reassessment of developmental toxicity of pfhxa in mice. International Journal of Toxicology, 38(3), 183–191. https://doi.org/10.1177/1091581819837904
  31. Wang, Y., Niu, J., Zhang, L., & Shi, J. (2014). Toxicity assessment of perfluorinated carboxylic acids (Pfcas) towards the rotifer Brachionus calyciflorus. Science of The Total Environment, 491–492, 266–270. https://doi.org/10.1016/j.scitotenv.2014.02.028.
  32. Ali, J. M., Roberts, S. M., Gordon, D. S., & Stuchal, L. D. (2019). Derivation of a chronic reference dose for perfluorohexane sulfonate (Pfhxs) for reproductive toxicity in mice. Regulatory Toxicology and Pharmacology, 108, 104452. https://doi.org/10.1016/j.yrtph.2019.104452
  33. Viberg, H., Lee, I., & Eriksson, P. (2013). Adult dose-dependent behavioral and cognitive disturbances after a single neonatal PFHxS dose. Toxicology, 304, 185–191. https://doi.org/10.1016/j.tox.2012.12.013
  34. Lee, I., & Viberg, H. (2013). A single neonatal exposure to perfluorohexane sulfonate (Pfhxs) affects the levels of important neuroproteins in the developing mouse brain. NeuroToxicology, 37, 190–196. https://doi.org/10.1016/j.neuro.2013.05.007
  35. Vogs , C., Johanson, G., Näslund, M., Wulff, S., Sjödin, M., Hellstrandh, M., Lindberg, J., & Wincent, E. (2019). Toxicokinetics of perfluorinated alkyl acids influences their toxic potency in the zebrafish embryo(danio rerio). Environmental Science & Technology, 53(7), 3898–3907. https://doi.org/10.1021/acs.est.8b07188
  36. Chang, S., Butenhoff, J. L., Parker, G. A., Coder, P. S., Zitzow, J. D., Krisko, R. M., Bjork, J. A., Wallace, K. B., & Seed, J. G. (2018). Reproductive and developmental toxicity of potassium perfluorohexanesulfonate in CD-1 mice. Reproductive Toxicology, 78, 150–168. https://doi.org/10.1016/j.reprotox.2018.04.007
  37. Butenhoff, J. L., Chang, S.-C., Ehresman, D. J., & York, R. G. (2009). Evaluation of potential reproductive and developmental toxicity of potassium perfluorohexanesulfonate in Sprague Dawley rats. Reproductive Toxicology, 27(3), 331–341. https://doi.org/10.1016/j.reprotox.2009.01.004
  38. Cassone, C. G., Vongphachan, V., Chiu, S., Williams, K. L., Letcher, R. J., Pelletier, E., Crump, D., & Kennedy, S. W. (2012). In ovo effects of perfluorohexane sulfonate and perfluorohexanoate on pipping success, development, mrna expression, and thyroid hormone levels in chicken embryos. Toxicological Sciences, 127(1), 216–224. https://doi.org/10.1093/toxsci/kfs072
  39. Kim, S.-J., Heo, S.-H., Lee, D.-S., Hwang, I. G., Lee, Y.-B., & Cho, H.-Y. (2016). Gender differences in pharmacokinetics and tissue distribution of 3 perfluoroalkyl and polyfluoroalkyl substances in rats. Food and Chemical Toxicology, 97, 243–255. https://doi.org/10.1016/j.fct.2016.09.017
  40. Cassone, C. G., Taylor, J. J., O’Brien, J. M., Williams, A., Yauk, C. L., Crump, D., & Kennedy, S. W. (2012). Transcriptional profiles in the cerebral hemisphere of chicken embryos following in ovo perfluorohexane sulfonate exposure. Toxicological Sciences, 129(2), 380–391. https://doi.org/10.1093/toxsci/kfs219
  41. Gordon, S. C. (2011). Toxicological evaluation of ammonium 4,8-dioxa-3H-perfluorononanoate, a new emulsifier to replace ammonium perfluorooctanoate in fluoropolymer manufacturing. Regulatory Toxicology and Pharmacology, 59(1), 64–80. https://doi.org/10.1016/j.yrtph.2010.09.008
  42. Bogdanska, J., Sundström, M., Bergström, U., Borg, D., Abedi-Valugerdi, M., Bergman, Å., DePierre, J., & Nobel, S. (2014). Tissue distribution of 35S-labelled perfluorobutanesulfonic acid in adult mice following dietary exposure for 1-5days. Chemosphere, 98, 28–36. https://doi.org/10.1016/j.chemosphere.2013.09.062 
  43. Chen, F., Wei, C., Chen, Q., Zhang, J., Wang, L., Zhou, Z., Chen, M., & Liang, Y. (2018). Internal concentrations of perfluorobutane sulfonate (PFBS) comparable to those of perfluorooctane sulfonate (PFOS) induce reproductive toxicity in Caenorhabditis elegans. Ecotoxicology and Environmental Safety, 158, 223–229. https://doi.org/10.1016/j.ecoenv.2018.04.032
  44. Chen, L., Lam, J. C. W., Hu, C., Tsui, M. M. P., Lam, P. K. S., & Zhou, B. (2019). Perfluorobutanesulfonate exposure skews sex ratio in fish and transgenerationally impairs reproduction. Environmental Science and Technology, 53(14), 8389–8397. https://doi.org/10.1021/acs.est.9b01711
  45. Chen, L., Tsui, M. M. P., Hu, C., Wan, T., Au, D. W. T., Lam, J. C. W., Lam, P. K. S., & Zhou, B. (2019). Parental Exposure to Perfluorobutanesulfonate Impairs Offspring Development through Inheritance of Paternal Methylome. Environmental Science and Technology, 53(20), 12018–12025. https://doi.org/10.1021/acs.est.9b03865
  46. Chen, L., Tsui, M. M. P., Shi, Q., Hu, C., Wang, Q., Zhou, B., Lam, P. K. S., & Lam, J. C. W. (2018). Accumulation of perfluorobutane sulfonate (PFBS) and impairment of visual function in the eyes of marine medaka after a life-cycle exposure. Aquatic Toxicology, 201, 1–10. https://doi.org/10.1016/j.aquatox.2018.05.018
  47. Hagenaars, A., Vergauwen, L., De Coen, W., & Knapen, D. (2011). Structure-activity relationship assessment of four perfluorinated chemicals using a prolonged zebrafish early life stage test. Chemosphere, 82(5), 764–772. https://doi.org/10.1016/j.chemosphere.2010.10.076
  48. Lou, Q. Q., Zhang, Y. F., Zhou, Z., Shi, Y. L., Ge, Y. N., Ren, D. K., Xu, H. M., Zhao, Y. X., Wei, W. J., & Qin, Z. F. (2013). Effects of perfluorooctanesulfonate and perfluorobutanesulfonate on the growth and sexual development of Xenopus laevis. Ecotoxicology, 22(7), 1133–1144. https://doi.org/10.1007/s10646-013-1100-y
  49. Marziali, L., Rosignoli, F., Valsecchi, S., Polesello, S., & Stefani, F. (2019). Effects of Perfluoralkyl Substances on a Multigenerational Scale: A Case Study with Chironomus riparius (Diptera, Chironomidae). Environmental Toxicology and Chemistry, 38(5), 988–999. https://doi.org/10.1002/etc.4392
  50. Sant, K. E., Venezia, O. L., Sinno, P. P., & Timme-Laragy, A. R. (2019). Perfluorobutanesulfonic acid disrupts pancreatic organogenesis and regulation of lipid metabolism in the Zebrafish, Danio rerio. Toxicological Sciences, 167(1), 157–171. https://doi.org/10.1093/toxsci/kfy237
  51. Domínguez, A., Salazar, Z., Betancourt, M., Ducolomb, Y., Casas, E., Fernández, F., Bahena, I., Salomón, A., Teteltitla, M., Martínez, R., Chaparro, A., Cuapio, P., Salazar-López, C., & Bonilla, E. (2019). Effect of perfluorodecanoic acid on pig oocyte viability, intracellular calcium levels and gap junction intercellular communication during oocyte maturation in vitro. Toxicology in Vitro, 58(April), 224–229. https://doi.org/10.1016/j.tiv.2019.03.041 
  52. Berntsen, H. F., Bjørklund, C. G., Audinot, J. N., Hofer, T., Verhaegen, S., Lentzen, E., Gutleb, A. C., & Ropstad, E. (2017). Time-dependent effects of perfluorinated compounds on viability in cerebellar granule neurons: Dependence on carbon chain length and functional group attached. NeuroToxicology, 63, 70–83. https://doi.org/10.1016/j.neuro.2017.09.005 
  53. Jo, A., Ji, K., & Choi, K. (2014). Endocrine disruption effects of long-term exposure to perfluorodecanoic acid (PFDA) and perfluorotridecanoic acid (PFTrDA) in zebrafish (Danio rerio) and related mechanisms. Chemosphere, 108, 360–366. https://doi.org/10.1016/j.chemosphere.2014.01.080 
  54. Johansson, N., Fredriksson, A., & Eriksson, P. (2008). Neonatal exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) causes neurobehavioural defects in adult mice. NeuroToxicology, 29(1), 160–169. https://doi.org/10.1016/j.neuro.2007.10.008 
  55. Vanden Heuvel, J. P., Kuslikis, B. I., & Peterson, R. E. (1992). Covalent binding of perfluorinated fatty acids to proteins in the plasma, liver and testes of rats. Chemico-Biological Interactions, 82(3), 317–328. https://doi.org/10.1016/0009-2797(92)90003-4 
  56. Vanden Heuvel, J. P., Kuslikis, B. I., Van Rafelghem, M. J., & Peterson, R. E. (1991). Disposition of perfluorodecanoic acid in male and female rats. Toxicology and Applied Pharmacology, 107(3), 450–459. https://doi.org/10.1016/0041-008X(91)90308-2 
  57. Bookstaff, R. C., Moore, R. W., Ingall, G. B., & Peterson, R. E. (1990). Androgenic deficiency in male rats treated with perfluorodecanoic acid. Toxicology and Applied Pharmacology, 104(2), 322–333. https://doi.org/10.1016/0041-008X(90)90306-F 
  58. Harris, M. W., Uraih, L. C., & Birnbaum, L. S. (1989). Acute toxicity of perfluorodecanoic acid in C57BL/6 mice differs from 2,3,7,8-tetrachlorodibenzo-p-dioxin. Toxicological Sciences, 13(4), 723–736. https://doi.org/10.1093/toxsci/13.4.723 
  59. Harris, M. W., & Birnbaum, L. S. (1989). Developmental toxicity of perfluorodecanoic acid in C57BL/6N mice. Toxicological Sciences, 12(3), 442–448. https://doi.org/10.1093/toxsci/12.3.442 
  60. Gutshall, D. M., Pilcher, G. D., & Langley, A. E. (1989). Mechanism of the serum thyroid hormone lowering effect of perfluoro-n-decanoic acid (Pfda) in rats. Journal of Toxicology and Environmental Health, 28(1), 53–65. https://doi.org/10.1080/15287398909531328
  61. Van Rafelghem, M. J., Mattie, D. R., Bruner, R. H., & Andersen, M. E. (1987). Pathological and hepatic ultrastructural effects of a single dose of perfluoro-n-decanoic acid in the rat, hamster, mouse, and Guinea pig. Toxicological Sciences, 9(3), 522–540. https://doi.org/10.1093/toxsci/9.3.522
  62. Van Rafelghem, M. J., Inhorn, S. L., & Peterson, R. E. (1987). Effects of perfluorodecanoic acid on thyroid status in rats. Toxicology and Applied Pharmacology, 87(3), 430–439. https://doi.org/10.1016/0041-008X(87)90248-1
  63. Langley, A. E., & Pilcher, G. D. (1985). Thyroid, bradycardic and hypothermic effects of perfluoro-n-decanoic acid in rats. Journal of Toxicology and Environmental Health, 15(3–4), 485–491. https://doi.org/10.1080/15287398509530675
  64. Boujrad, N., Vidic, B., Gazouli, M., Culty, M., & Papadopoulos, V. (2000). The peroxisome proliferator perfluorodecanoic acid inhibits the peripheral-type benzodiazepine receptor (PBR) expression and hormone-stimulated mitochondrial cholesterol transport and steroid formation in Leydig cells. Endocrinology, 141(9), 3137–3148. https://doi.org/10.1210/endo.141.9.7678 
  65. Benninghoff, A. D., Orner, G. A., Buchner, C. H., Hendricks, J. D., Duffy, A. M., & Williams, D. E. (2012). Promotion of hepatocarcinogenesis by perfluoroalkyl acids in rainbow trout. Toxicological sciences : an official journal of the Society of Toxicology, 125(1), 69–78. https://doi.org/10.1093/toxsci/kfr267
  66. Benninghoff, A. D., Bisson, W. H., Koch, D. C., Ehresman, D. J., Kolluri, S. K., & Williams, D. E. (2011). Estrogen-like activity of perfluoroalkyl acids in vivo and interaction with human and rainbow trout estrogen receptors in vitro. Toxicological sciences : an official journal of the Society of Toxicology, 120(1), 42–58. https://doi.org/10.1093/toxsci/kfq379
  67. Ishibashi, H., Yamauchi, R., Matsuoka, M., Kim, J. W., Hirano, M., Yamaguchi, A., Tominaga, N., & Arizono, K. (2008). Fluorotelomer alcohols induce hepatic vitellogenin through activation of the estrogen receptor in male medaka (Oryzias latipes). Chemosphere, 71(10), 1853–1859. https://doi.org/10.1016/j.chemosphere.2008.01.065 

Modified Mu Opioid Receptors Lead to Analgesia Without Physical Dependence

By Neha Madugala, Neurobiology, Physiology, and Behavior ‘21

Author’s Note: I wrote this literature review for my UWP104F class to assess new opioid-based medications for pain-relief. While opioids are the best known pain relievers we currently have, they have the severe risks of addiction and overdose. This paper analyzes literature that attempts to amplify the analgesic (pain-relief) properties of opioids, while minimizing their addictive potential. 

 

Introduction

As the opioid epidemic grows, opioids are becoming increasingly synonymous with addiction and overdose. While opioids have immense pain-relief properties, their use has been limited due to their major risks. The potential for addiction lies in the interaction between opioids and the mu-opioid receptor. Scientists are working to create a modified receptor that can have these analgesic effects but have limited risk. These findings could aid in the development of safer but effective pain-relief medications. 

Background

Drug addiction is a chronic relapsing disorder that occurs through repeated exposure to the drug, leading to physiological changes in brain chemistry [6]. While initial use is associated with improved well-being and feelings of euphoria, this repeated use in addition to environmental factors and genetics can lead to modifications in the endogenous opioid system, or the body’s natural pain killers, and alterations of stress physiology through hormonal imbalance [6, 7]. These homeostatic changes deregulate brain reward pathways, resulting in tolerance and dependence [7]. 

Opioids have a significantly higher rate of relapse compared to other addictive drugs since they induce strong physical dependence [7] and craving [7]. As a result, scientists have extensively studied the mu-opioid receptor (MOPr), which directly binds to opioids and indirectly binds to other addictive drugs, such as alcohol, cannabinoids, and nicotine [6]. Current research is focused on understanding the mechanism of the MOPr. While scientists agree that this mechanism plays a role in physical dependence, it is unclear what part of this pathway is responsible for these observed effects. 

Opioids act as agonists at the MOPr. Agonists modify a receptor through intrinsic efficacy and affinity. Affinity determines how well a ligand is able to bind to the active site of a receptor and intrinsic efficacy is a measure of how well a ligand is able to stabilize the receptor in its active conformation [1]. Intrinsic efficacy is particularly important for the MOPr because the MOPr is strongly agonist-dependent [6]. For instance, morphine acts as a full agonist at the MOPr, inducing the maximal effect. As a result, morphine is commonly used to study the function of this receptor and its role in addiction. 

At the MOPr, opioids bind to the active site inducing a conformational change and activating the receptor. The MOPr is a G protein-coupled receptor (GPCR), which is a type of receptor where activation leads to secondary pathway signaling. As a result, binding of a ligand to the MOPr causes secondary pathways to be activated, resulting in downstream signaling effects. Specifically, the MOPr is a Gi-coupled GPCR, so it inhibits the enzyme adenylyl cyclase, which converts ATP to cAMP. As a result, opioid binding inhibits the production of cAMP. 

This effect is brief. MOPr activation promotes translocation of β-arrestin from the cytosol to the plasma membrane. MOPr is rapidly phosphorylated by GPCR kinases (GRKs). This phosphorylation increases the affinity of β-arrestin to the MOPr [6]. β-arrestin binds to the MOPr. This binding uncouples the MOPr from the Gi-coupled GPCR, which halts the inhibition of cAMP production. This uncoupling further halts the signaling pathways and results in desensitization of the MOPr, since the opioid can no longer induce downstream effects.

β-arrestin also recruits components of the endocytic machinery [2] to engulf the MOPr into the cell. The desensitized receptor is internalized within the cell via endocytosis [2]. Endocytosis plays an important role in engulfing the desensitized receptor, which is no longer functional, and placing it back into the plasma membrane resensitized, or functional. This rapid resensitization process is important for having a consistent supply of available receptors for ligand binding. 

Naloxone acts to block agonists of the MOPr and is used as a treatment for drug overdose, and to induce withdrawal in experimental models. As an antagonist, naloxone has zero intrinsic efficacy, so it does not modify the constitutive activity of the receptor.  Essentially antagonists do not activate any additional pathways but have an affinity for the active site of the respective receptor [1]. As a result, naloxone competes with agonists for the binding site and prevents agonists from inducing an effect on the MOPr. Their ability to compete is dependent on their level of affinity. Opioid antagonists are used in drug experiments to quickly stop drug administration in the brain to assess signs of physical dependence. This method is efficient because it can prevent agonists from working, even when the agonist is present in the bloodstream. For this reason, antagonists are also administered following overdose to reverse opioid-induced respiratory depression, where the brain stops sending signals to the body to breathe [4]. 

β-arrestin and Physical Dependence

Enkephalins, an endogenous opioid, at the MOPr activate the Gi-coupled GPCR and β-arrestin in equal amounts. As a result, enkephalins are “unbiased.” However, many addictive opioids, such as morphine, act as biased agonists signaling the Gi-coupled GPCR and β-arrestin asymmetrically [1]. At the MOPr, scientists hypothesize that “G-protein signaling [is] responsible for opioid-induced analgesia, while [β-arrestin is] responsible for the adverse effects of mu-receptor activation” [9]. 

In a study in the Nature Journal of β-arrestin-2 knockout mice by Bohn et al., they studied the development of antinociception tolerance following daily administration of a moderate dose of morphine (10 mg/kg) for nine days [3]. They conducted this experiment to determine whether chronic morphine use can diminish antinociception over time, a sign of addiction. They used wild-type mice as controls. To control for genetic variation, they crossed over eight generations of mice that were heterozygous for β-arrestin-2. This allowed them to develop wild-type and knockout mice (through the homozygous progeny) that were “age-matched, 3—5-month-old male siblings weighing between 20 and 30 g [3]. The wild-type mice had a significantly diminished response to morphine administration by day five. In contrast, the knockout mice had comparable antinociception throughout the entire experimental period [3]. These findings suggest that β-arrestin presence has a significant role in the development of antinociceptive tolerance. 

Moreover, β-arrestin plays multiple roles in the MOPr trafficking process. To further assess these results, researchers studied one aspect of β-arrestin, promoting endocytosis. Kim et al. hypothesized that over time morphine binding to the MOPr led to diminished antinociception, tolerance, and dependence due to morphine’s inability “to promote substantial receptor endocytosis” [10]. They generated knockout mice by genetically modifying the MOPr at exon 3 to create an experimental receptor (rMOP-R) that would be more effective at resensitizing the receptor through endocytosis [10]. They used wild-type mice as a control. 

The mice with the rMOP-R had enhanced and prolonged analgesic effects compared to the wild-type mice with the MOP-R. They suggested that these results were due to the rMOP-R being active for longer due to quicker resensitization [10]. Furthermore, they assessed tolerance and dependence over both a short-term experiment (one day) and a long-term experiment (five days). The wild-type mice displayed both acute and chronic antinociceptive tolerance to morphine, as well as withdrawal responses to any administration of naloxone following morphine administration. The knockout mice did not develop acute or chronic antinociceptive tolerance to morphine and showed much fewer withdrawal responses to administration of naloxone following morphine administration [10]. 

Kim et al. did these experiments with endogenous opioids (DAMGO), morphine, and methadone with acts similarly to endogenous opioids. They found a significant difference between the wild-type and knockout mice for morphine administration only [10]. This supports their hypothesis since DAMGO and methadone already have enhanced endocytosis. 

These results suggest that enhanced endocytosis of the MOPr can help alleviate tolerance and signs of physical dependence while maintaining the antinociceptive effects. While β-arrestin functions to recruit the endocytic machinery, it also turns off the MOPr by desensitizing the receptor. Since the MOPr is strongly agonist-dependent, morphine acting at this receptor results in an increased period of desensitization. By diminishing this off period through enhanced endocytosis, the rMOP-R receptor leads to quicker resensitization, alleviating signs of physical dependence [10]. 

To further explore this hypothesis, Berger and Whistler conducted a similar study to Kim et al. by comparing the knockout mice with rMOP-R to wild-type mice with the MOPr in a conditioned place preference (CPP) paradigm and self-administration study. A CPP paradigm is when the mice are placed in a room with two sides that are decorated in distinct manners. On one side they are administered morphine, while they are not on the other side. Preference for morphine is determined by which room they spend more time in. For the CPP paradigm, the rMOP-R mice displayed greater CPP at lower doses and the wild-type mice displayed greater CPP at higher doses [2]. This indicates that the knockout mice had a large rewarding effect at low doses, suggesting that smaller doses of morphine elicited a larger effect in the knockout mice compared to the wild-type mice. 

Furthermore, they assessed how these mice lines differed for additional determinants of addiction in a self-administration study. For each operant session, the mice were allowed to administer morphine on the first day, morphine and water for the next four days, and were given only water on the last two days of the experiment [2]. They assessed four factors: “high motivation to obtain drug,” “futile drug-seeking,” “persistent drug-seeking in the face of adverse consequences,” and “reduced preference for alternative rewards” [2]. 

Berger and Whistler found that when morphine was administered into the lever at regular intervals, the knockout mice learned these intervals while the wild-type mice attempted to administer the drug more often by pressing the lever, even though it was in between the intervals [2]. They further assessed lever presses when accompanied by an electric shock or in the presence of an alternate reward, saccharin. The wild-type mice administered the drug more often and showed a greater preference for morphine respectively for these experiments compared to the knockout mice [2]. These results indicate that the enhanced endocytosis and quicker resensitization of the MOPr helps alleviate the adverse effects of addiction beyond physical dependence. 

G-Protein Biased Agonists 

Based on these findings, researchers hypothesize that creating drugs that are G-protein biased agonists could help improve the antinociceptive effects of opioids while diminishing the adverse effects of delayed desensitization due to β-arrestin [9]. There is ongoing research to develop G-protein-biased agonists of the MOPr. For instance, oliceridine, a G-protein-biased agonist, is currently in Phase 3 of clinical trials [8]. However, current research is bringing into question whether only β-arrestin is responsible for the adverse effects of addiction [8]. 

There is now evidence suggesting that “MOPr activation in [the preBotzinger (preBotC) and Kolliker-Fuse (KF) neurons] … inhibits neuronal activity via G protein signaling” [8]. The preBotC and KF neurons are located in regions of the brain associated with respiratory control [8]. They also found that the activation of GRKs, which promotes arrestin binding to Gi-coupled GPCRs, is mediated by G protein signaling [8].

In a study in the British Journal of Pharmacology of morphine-induced respiratory depression independent of β-arrestin-2 by Kliewer et al., they used β-arrestin knockout mice to assess respiratory depression when administered an opioid. This experiment was conducted in three laboratories, located in Jena, Germany; Sydney, Australia; and Bristol, United Kingdom [11]. Each laboratory used a similar experimental set-up with slight variations. 

They all found a “dose-dependent depression of respiratory rate by morphine” [11]. The laboratory in Jena used a nose-out plethysmography system; the laboratories in Sydney and Bristol used whole-body plethysmography [11]. (Plethysmography methods assess the difference in the volume of air present in the lungs prior to and post-exhaling.) 

While biased agonism has been suggested as a possible mechanism to isolate the analgesic properties of opioids from the adverse effects, these studies point out weaknesses in this model. First, the initial study assessing β-arrestin-2 knockout mice has not been extensively repeated to verify accuracy and the pathway for respiratory depression cannot be isolated to only β-arrestin [11]. This new evidence indicates that both G-protein signaling and β-arrestin play a role in the physical dependence on opioids. However, more research is needed to determine the extent of how much each protein influences these physiological symptoms. 

Discussion

While the original findings indicated that only β-arrestin is responsible for the adverse effects of opioid use, new research suggests that these effects cannot be easily isolated to just β-arrestin. The results indicate that β-arrestin plays a role in tolerance and dependence, while G-protein plays a role in respiratory depression during an overdose. More research on G-protein signaling and its connection to the dopamine reward pathway is necessary to understand the extent of its involvement in the MOPr trafficking system. Furthermore, more research is needed to replicate the studies done on β-arrestin-2 knockout mice because these studies have not been extensively replicated, bringing into question the accuracy of these past findings. Also, our understanding of the role of β-arrestin-2 in the desensitization of the MOPr is based on research done in HEK 293 cells, found in the human embryonic kidney; these results have not been replicated in neurons [5], yet the MOPr trafficking system occurs within neurons. Overall, further research is needed to establish the reliability of past findings on β-arrestin and to understand the adverse effects of G-protein signaling. The latter is especially important because current research is focused on developing G-protein-biased agonists to act as analgesics; however, these new analgesics may still pose the risk of respiratory depression.  

Conclusion

Current research of the mu-opioid receptor trafficking system indicates that both β-arrestin and Gi-coupled GPCR are responsible for the adverse effects of opioids, including tolerance, dependence, and respiratory depression. More extensive research is required to determine the exact roles of the β-arrestin and Gi-coupled GPCR, while also verifying the results of past studies. These findings can help determine the risk of respiratory depression in the development of new analgesics and extend our understanding of the development of tolerance and withdrawal in addiction. Moreover, these results can help diminish the risk of more potent opioids, while acting as effective pain medications. 

 

References

  1. Berg, Kelly A, and William P. Clarke. “Making Sense of Pharmacology: Inverse Agonism and Functional Selectivity.” International Journal of Neuropsychopharmacology, vol. 21, no. 10, 2018, pp. 962-977. NIH, https://pubmed.ncbi.nlm.nih.gov/30085126/. 
  2. Berger, Amy C, and Jennifer L. Whistler. “Morphine-Induced Mu Opioid Receptor Trafficking Enhances Reward yet Prevents Compulsive Drug Use.” EMBO Molecular Medicine, vol. 3, no. 7, 2011, pp. 385-97. NCBI, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394511/.
  3. Bohn, Laura M., et al. “Mu-Opioid Receptor Desensitization by β-arrestin-2 Determines Morphine Tolerance but not Dependence.” Nature, vol. 408, 2000, pp. 720-23. NIH, https://pubmed.ncbi.nlm.nih.gov/11130073/. 
  4. Bubier, Jason A., et al. “Genetic Variation Regulates Opioid-Induced Respiratory Depression in Mice.” Nature Research, vol. 10, no. 14, 2020, pp. 1-15. Nature, https://www.nature.com/articles/s41598-020-71804-2.
  5. Connor, Mark, et al. “Mu-Opioid Receptor Desensitization: Is Morphine Different?” British Journal of Pharmacology, vol. 143, 2004, pp. 685-696. Nature Publishing Group, doi:10.1038/sj.bjp.0705938.
  6. Contet, Candice, et al. “Mu Opioid Receptor: A Gateway to Drug Addiction.” Current Opinion in Neurobiology, vol. 14, 2004, pp. 370-78. Science Direct, https://www.sciencedirect.com/science/article/pii/S0959438804000728. 
  7. Gerrits, Mirjam, et al. “Drug Dependence and the Endogenous Opioid System.” European NeuroPsychoPharmacology, vol. 13, 2003, pp. 424-434. Elsevier Ltd., doi:10.1016/j.euroneuro.2003.08.003.
  8. Gillis, Alexander, et al. “Critical Assessment of G Protein-Biased Agonism at the Mu-Opioid Receptor.” Cell Press Reviews, vol. 41, no. 12, 2020, pp. 947-59. Elsevier Ltd., https://doi.org/10.1016/j.tips.2020.09.009.
  9. Groom, Sam, et al. “A Novel G Protein-Biased Agonist at the Mu Opioid Receptor Induces Substantial Receptor Desensitisation Through G Protein-Coupled Receptor Kinase.” British Pharmacological Society, 2020, pp. 1-15. Wiley Online Library, doi:10.1111/bph.15334. 
  10. Kim, Joseph A., et al. “Morphine-Induced Receptor Endocytosis in a Novel Knockin Mouse Reduces Tolerance and Dependence.” Cell Press Journal, vol. 18, no. 2, 2008, pp. 129-35. NIH, https://pubmed.ncbi.nlm.nih.gov/18207746/. Kliewer, Andrea, et al. “Morphine-Induced Respiratory Depression is Independent of β-arrestin-2 Signalling.” British Journal of Pharmacology, vol. 177, 2020, pp. 2923-2931. Wiley Online Library, https://bpspubs.onlinelibrary.wiley.com/doi/10.1111/bph.15004.

Potential Methods of Life Detection on Ocean Worlds

By Ana Menchaca, Biochemistry and Molecular Biology ‘20

Author’s Note: As a biochemistry major who is interested in pursuing astrobiology research, I initially wrote this literature review for an assignment in my Writing in Biology course. Methods of life detection and what we know about life is a field in which we still have much to discover and explore, given Earth as our only example, and I hope to be involved in this exploration myself in the future.

 

Abstract

Ocean worlds, such as Enceladus, Saturn’s largest moon, provide intriguing environments and the potential for life as we continue to explore the Solar System. Organic compounds have been discovered in plumes erupting from the moon during flybys and point towards the presence of amino acids and other precursors of life. The data collected from these flybys, in turn, has been used to calculate the theoretical amounts of amino acids present in the oceans of Enceladus. While this data is intriguing, it relies on a limited definition of life, based on organisms and macromolecules that have only been observed on Earth. Other methods, including using nucleic acids or nanopores for detection, have been proposed. Nucleic acids utilize binding to identify a broad spectrum of compounds, while nanopores utilize the measurement of ionic flow. These alternative methods allow for a broader spectrum of compound detection than terran-based methods, creating the potential to detect unfamiliar kinds of life. Research into more holistic detection should continue.

Keywords: astrobiology, life detection, planetary exploration, biosignatures

 

Introduction

The search for life elsewhere in the Solar System is becoming increasingly relevant, and more importantly, feasible. Icy moons, such as Europa, Titan, and Enceladus, have been identified as holding the greatest potential for extraterrestrial life within the Solar System [1]. Europa and Enceladus, with seas below icy crusts, have geysers with unidentified fluctuations, along with evidence of tidal warming and geologic activity [2]. The Cassini spacecraft identified these geysers on Enceladus during flyby in 2006, spouting from four specific fractures on the surface of the moon [3]. Analysis of the vapors produced show that they mainly consist of water, along with CO2, N2, CO, CH4, salts, other organic compounds, and silica particulates [3, 4]. This points towards evidence of hydrothermal activity, the movement of heated water, which has the potential to provide necessary energy for life [4]. Additionally, the discovery of volatile aliphatic hydrocarbons in these plumes potentially indicate some degree of organic evolution within the seas of Enceladus [4].

However, there is no consensus yet on how to detect and identify life [1, 2]. Some scientists propose looking for life based on the shared ancestry hypothesis, which proposes all life shares the same genetic ancestry [2]. Others propose there is a potential for extraterrestrial life to present variations from terran life that we may neither be able to recognize nor detect with our current methods of biochemical detection [5]. Experimentally, the potential for nucleic acids based on different backbones has already been identified [5]. Here, we examine the range of proposed methods for identifying extraterrestrial life. 

 

Proposed theories and methods based on current knowledge of life

Collection of amino acids

Current data collected from Enceladus’ plumes presents organic compounds that provide potential evidence of amino acid synthesis taking place in the oceans of the moon. Steel et al. used the thermal flux at the moon’s South Polar Terrain (SPT) to predict the hydrogen produced by hydrothermal activity. The predicted rates of production ranged between 0.63 and 33.8 mol/s of H2, and from there, amino acid production rates were estimated to be between 8.4 and 449.4 mmol/s [4]. Annual biomass production was also modelled in these calculations and estimated at 4 · 10to 2 · 106 kg/year, compared to 1014 kg/year on Earth. These estimates, however, are dependent on the environment being an abiotic, steady state ocean; the actual production rates could be different if there is life present in Enceladus’ ocean [4]. 

While this limits our predictions of Enceladus’ true environment, it still provides a basis that can be extrapolated for use in the design of modules to be sent out. One such module that has been proposed is the Enceladus Organic Analyzer, which is designed to analyze amino acids through chain length variations [3]. To properly collect and analyze the amino acids proposed to be in Enceladus’ oceans, there are several requirements. The sample must be collected from the subsurface ocean with minimal degradation, isomerization, racimerization, and contamination of biological molecules and amino acids [3]. A collection chamber made of aluminum has been modeled, designed to reduce the thermal heating caused by collection of samples, in order to best preserve them. If the moon contains bacteria as postulated, this design will lyse and kill collected cells through either heat or shock but release their more stable chemical components for analysis [3]. This depends highly upon current knowledge as a starting place, focusing with a limited scope on amino acid and cell identification. Another such method using cell identification is digital holographic microscopy. 

Digital holographic microscopy

The development and improvements of microscopy, while beneficial, depend heavily on the assumption that life in the same form as terran cells will be found. Investigators propose digital holographic microscopy (DHM) as a more efficient alternative over traditional light microscopy [1]. This technology produces a 100-fold improvement in the depth of field and is able to monitor both intensity and phase of images. However, even with the increase in resolution, differentiation of cells and cell-shaped structures is difficult, even before taking into account potential differences in extraterrestrial life. Refraction, an emerging field, was able to differentiate experimentally between crystalline structures and cells in the study’s Arctic samples. While the technology can be miniaturized and discriminate between cells and minerals, it depends highly on actual capture of a sufficient number of cells from plumes. This experimental data was obtained using dye-less techniques, which still function in the context of organisms without DNA or RNA, and refraction with the potential to differentiate structures [1]. DHM is both useful for detection of cells based on collected data and for the potential discovery of organisms without nucleic acids as we know them. 

 

Expanding outside the current knowledge of life

Detection using nucleic acids
Other experiments and proposals, while not explicitly targeting life outside the current perceptions, propose a more holistic collection of data. This carries the potential of identifying life outside our current scope, as opposed to focusing directly on known amino acids and cells. Using a broader concept of nucleic acids as a means of detection and identification is one such method. 

Oligonucleotides, through forming secondary and tertiary structures, have specificity and affinity to a wide variety of molecules, both organic and inorganic [2]. Even at a length of only 15 base pairs and within complex mixtures, these molecules can bind to what is being analyzed, or the analytes. Systematic evolution of ligands by exponential enrichment (SELEX) is a process that can identify oligonucleotides that bind very specifically to analytes. However, this method proposes the use of low affinity and low specificity nucleic acids that are typically discarded in this process. Unlike antibodies, this method requires no prior knowledge of the surface attributes or the three-dimensional structure of the molecule that is being bound. Through accumulating a wide range of binding sequences and statistical analysis, a vast number of compounds can be collected and environmental variations identified. Additionally, this method posits that the optimal means of capturing sequences is through proximity ligation assay (PLA), a technique currently used in scientific fields. PLA purifies the binding species based on ligation and amplification, producing a lower background than sieving, which separates based on size. It is also capable of capturing a vast range of sequences and structures, including inorganic, organic, or polymeric molecules [2], and thus is more capable of providing holistic results.

 

Nanopore-based sensing

Nanopore-based sensing, presented as an alternative to current methods, detects and analyzes genetic information carriers in watery systems without making assumptions about its chemical composition [5]. This system relies upon the restrictions placed on these sorts of compounds within watery systems, as the repeating charge of backbones keeps polymer strands from folding and favors solubility in water. A nanopore is a hole with a diameter of a few nanometers, surrounded by an insulating membrane within two chambers containing an electrolyte solution. Due to its diameter, only single-stranded DNA can pass through the nanopore, allowing for slow movement and characteristic signals that produce data clearly distinguishable from other molecular data. This method can detect and analyze molecules by measuring the ionic flow across the membrane. While biological nanopores are able to detect and resolve individual terran bases, nonbiological, solid-state nanopores provide the same function, avoiding the limitations of detecting terran molecules that may be present in biological nanopores. Graphene, with its crystalline form, can have its membrane adjusted to only accommodate one nucleotide at a time or can be sculpted to produce varying sizes of nanopores. This could allow for the detection of other polymers with chemical and sterical properties that vary from currently known polymers. This approach has the potential to analyze a broad range of molecules without any assumptions regarding the external structure’s outside charge and linearity. Few identified nonbiological polymers are structured this way, so any data picked up by nanopores would be significant [5].

There are, however, limitations to this approach. Nucleic acids have high electroporation speeds, making it necessary to find methods of slowing these speeds down for accuracy [5]. Electroporation uses an electrical charge to make the cell membrane more permeable. Potential methods include control through physical factors, such as temperature, salinity, and viscosity. Conditions of collection on other planets also pose the problem of extreme dilution of the target molecules, which depends on a large number of variables [5]. 

 

Conclusion

Radiation and stability are major concerns in moving forward with any sort of data collection from extraterrestrial worlds. Mechanisms and samples are potentially open to the detrimental effects of extreme vacuum and solar radiation [5]. These problems should be addressed in conjunction with the technology actually being used for analysis to produce the most beneficial results. Some of these issues have been addressed to some extent, such as using microfluidics for collection because they are unaffected by the vacuum of space due to their own internal surface tension [3]. However, these problems need to be explored further in all cases to ensure that each method can function in uncontrolled or non-terran environments.

The presented data indicates potential for the existence of amino acids in these environments. Even though prediction and detection of these amino acids seems a logical step forward, the development of further, broader technology for life detection should also be pursued. Current knowledge is limited by the qualities of terran life; while that is a well-supported starting point, methods that leave open the potential of deviation from this point may allow for the detection of otherwise overlooked forms of life. Moving forward, it seems only logical to combine these methods that can detect both the known and the unknown, allowing scientists to gather the widest possible array of data in future missions, especially on promising worlds like Enceladus. 

 

References

  1. Bedrossian M, Lindensmith C, Nadeau JL. 2016. Digital Holographic Microscopy, a Method for Detection of Microorganisms in Plume Samples from Enceladus and Other Icy Worlds. Astrobiology 17(9):913–925.
  2. Johnson SS, Anslyn EV, Graham HV, Mahaffy PR, Ellington AD. 2018. Fingerprinting Non-Terran Biosignatures. Astrobiology 18(7):915–922.
  3. Mathies RA, Razu ME, Kim J, Stockton AM, Turin P, Butterworth A. 2016. Feasibility of Detecting Bioorganic Compounds in Enceladus Plumes with the Enceladus Organic Analyzer. Astrobiology 17(9):902–912.
  4. Steel EL, Davila A, Mckay CP. 2017. Abiotic and Biotic Formation of Amino Acids in the Enceladus Ocean. Astrobiology 17(9):862–875. 
  5. Rezzonico F. 2014. Nanopore-Based Instruments as Biosensors for Future Planetary Missions. Astrobiology 14(4):344–351.

Environmental Effects of Habitable Worlds on Protein Stability

By Ana Menchaca, Biochemistry and Molecular Biology ‘20

Author’s Note: As a biochemistry major hoping to further pursue an academic career in astrobiological research, this paper jumped out at me when finding a topic for a class assignment. It goes to show just how many paths there are to take in investigating life elsewhere in the universe and how much we still have yet to discover and understand. 

 

The search for life elsewhere is a vast, challenging undertaking, and investigation of conditions on so deemed habitable worlds provides insight into our current understanding of the existence of life. The conditions for a world to be considered potentially habitable are similar to those of life on Earth. These conditions include a source of energy, common essential elements that make up life (carbon, hydrogen, nitrogen, oxygen, phosphorus, and sulfur), and a solvent for chemical interactions (e.g. H2O). Understanding how chemicals and molecular components might interact with these environments can provide us with a better understanding of what could actually hold the potential for life as we currently know it. One of these important molecular components is proteins. 

Research exploring protein stability on Saturn’s largest moon, Titan, published in November 2019, presents an early foray into these considerations. This research studies the implications of variable environmental conditions on protein interactions and how this could detect potentially habitable worlds, similar to Earth. The study makes a foray into studying whether the conditions deemed necessary on Earth are really necessary for the survival of proteins. Molecular dynamics simulations explored structural interactions based on our current knowledge of protein interactions, using the software package GROMACS [1]. 

Titan is one of these potentially habitable candidates in our solar system, a category that also includes several other moons: Europa, Enceladus, Ganymede, and Callisto. All of these moons are considered to have subsurface oceans present, conditions that have the potential for the presence of chemical building blocks, liquid H2O, and sources of energy. Models show that Titan’s subsurface oceans may contain hydrogen, carbon, nitrogen, and ammonia (ensuring that the oceans remain liquid), thus indicating the potential for Earth-like biochemistry [1]. 

Martin et al. explored the potential effects of Titan’s hypothesized environment on the integrity of biologically relevant molecules. Protein compactness, flexibility, and backbone dihedral angle distributions were measured. Because protein folding is affected by affinity and electrical interactions with the environment that they’re in, the difference in the conditions of Titan’s high-pressure subsurface oceans to those on Earth has the potential to affect the folding and behavior of relevant proteins [1]. Even on Earth, extremophiles in hydrothermal vents have varying versions of common proteins, something that could indicate the potential for novel protein conformations that perform similar functions in unique, more extreme conditions than those on Earth. The potential existence of these conformers, which still act and provide the same structures and functions of Earth proteins, broadens and changes our scope of what’s necessary and indicative of life. 

In comparing Titan-like conditions to Earth, Martin et al. observed variations in the behavior of selected proteins (which were selected to highlight common folding of alpha helices and beta sheets). Proteins are formed at various levels of structure: primary, secondary and tertiary. The primary structure is the amino acid sequence, secondary structure is created by interactions of the polypeptide with itself, and tertiary structure is the proteins three dimensional, overall folding. Alpha helices and beta sheets are the most prevalent secondary structures for proteins on Earth, and the complex interactions and stability of these structures drives many biochemical interactions. 

The Root-mean-square fluctuation, or how much the atoms fluctuated about their average position, of the proteins in Titan-like conditions was lower on average than that of the proteins on Earth, indicating less variability in structure in these conditions. Additionally, for one of the proteins, rather than not stabilizing into a specific secondary structure like on Earth, it instead settled into a pi helix conformation, a secondary structure that’s uncommon on Earth, as it is less stable [1]. Due to this lack of stability compared to alpha helices, they are typically found near functional sites.These varying secondary structures of proteins affect their ability to interact with other molecules and enzymes in complex ways, something that in the case of pi helices is less explored given their relative rarity on Earth. 

These results show that while beta-sheets show similar behavior and presence in Titan-like conditions as they do on Earth, there’s also a tendency towards less common conformations (pi helices). These results expose both this variation of protein conformation and shape in differing conditions, and the survivability of proteins in non-Earth environments. This shows the possibility of discovering life in forms we are unfamiliar with, while also proving proteins, a vital component of life, are capable of existing in extraterrestrial environments. This research helps prove that those planets deemed habitable really are such, and the further study of the specific conformations and interactions of these proteins could provide us with more specific knowledge of what we might identify elsewhere. While this research is an early exploration of potential conditions on Titan and potentially other bodies with subsurface oceans, it still opens the door for further studies of environmental effects on known life, thus expanding our understanding of the potential for life to exist elsewhere.

 

Sources

  1. Martin, Kyle P., Shannon M. Mackenzie, Jason W. Barnes, and F. Marty Ytreberg. “Protein Stability in Titans Subsurface Water Ocean.” Astrobiology 20, no. 2 (January 2020): 190–98. https://doi.org/10.1089/ast.2018.1972.
  2. Abrevaya, Ximena C., Rika Anderson, Giada Arney, Dimitra Atri, Armando Azúa-Bustos, Jeff S. Bowman, William J. Brazelton, et al. “The Astrobiology Primer v2.0.” Astrobiology 16, no. 8 (January 2016): 561–653. https://doi.org/10.1089/ast.2015.1460.

Novel Pathway Elucidates Potential for Nitric-Oxide Produced by Tumor-Associated Macrophages to Confer Resistance to Chemotherapy Drug Cisplatin

By Reshma Kolala, Biochemistry & Molecular Biology ‘22

Authors Note: This past summer I was given the incredible opportunity to work in the Thurmond Lab at the City of Hope where I investigated a point mutant of the Syntaxin 4 protein on -cell function and apoptosis. The following piece reviews a publication that was fundamental to both the understanding and methodology of my project. 

 

Introduction

Cisplatin (CDDP) is a widely used chemotherapy drug that induces apoptosis in solid tumor cells, which are cells that lack cysts or liquid areas such as carcinomas, sarcomas, and lymphomas. The platinum-based chemotherapeutic agent was popularized in the late 1970s as the antitumoral toxicity of platinum compounds became known for their clinical efficacy against solid tumors (1). Although initially promising, many patients suffer a relapse due to the development of cisplatin resistance, largely as a result of their ability to overcome the apoptogenic effects of the drug. To elucidate the underlying mechanisms behind the propagation of cancer progression and chemotherapy resistance, an understanding of the tumor microenvironment is crucial. The tumor microenvironment is comprised of a complex and dynamic milieu that surrounds stromal cells. Among these cells, tumor-associated macrophages (TAMs) represent the largest population of infiltrating inflammatory cells in malignant tumors. TAMs have been suggested to possess a tumor-promoting phenotype that drives multiple mechanisms, most notably tumor cell proliferation and drug resistance (2). Initially, TAMs are in the classically-activated M1 state, in which their proinflammatory characteristics disables tumor growth. As tumors mature, however, they switch to an alternatively-activated M2 state, promoting tumor development and immunosuppression. As M2-like TAMs are major contributors to chemotherapeutic resistance, they are frequently targeted for cancer immunotherapies. 

M2-like TAMs are capable of producing nitric oxide (NO) via expression of inducible NO synthase (iNOS). NO is an important cell signaling molecule that is critical for many physiological processes such as neurogenesis and angiogenesis (3). At low levels, NO displays cytoprotective properties, promoting tumor growth, but can be cytotoxic to tumor cells when produced at high levels (4). The cytoprotective tendency of NO has been linked to the inhibition of the sphingomyelin-metabolizing enzyme acid sphingomyelinase (A-SMase). Traditionally, the activation of A-SMase (most commonly by chemotherapeutic drugs such as CDDP) drives the hydrolysis of sphingomyelin to generate ceramide. Ceramide, in coalition with other molecules, forms a cluster that drives transmembrane signaling of apoptotic death to effectively kill tumor cells (5). By contrast, it has been found that at relatively low concentrations NO hinders the beneficial apoptotic effect of A-SMase, resulting in resistance to the chemotherapeutic drug CDDP. The elucidation of this mechanism is the focus of research conducted by Perrotta et al. in 2018. 

A study led by Perrotta et al. investigated the potential for NO, a byproduct of TAMs, to be responsible for the mechanism conferring resistance to CDDP (6). An increased concentration of intracellular NO leads to the activation of the membrane-bound protein Syntaxin 4 (STX4) via a pathway that involves the production of cGMP and activation of protein kinase G (PKG). As STX4 aids in the translocation of A-SMase, an enzyme involved in apoptosis, to the plasma membrane, a decrease in the STX4 protein would result in resistance to the intended apoptotic effect of CDDP (Figure 1). However, it was found that a point mutant of the STX4 protein, namely the STX4-S78A mutant, is unable to be phosphorylated by PKG due to the chemical nature of the alanine side chain. This prevents proteasomal degradation, thus leading to successful tumoral apoptosis.

Figure 1: Nitric Oxide (NO)-Mediated Resistance to Apoptotic Effect of Cisplatin

A schematic of the Nitric Oxide-mediated resistance to chemotherapeutic drug CDDP. The introduction of CDDP (1) leads to an increase in the intracellular concentration of NO in TAMs (tumor associated macrophages). (2). This leads to the generation of cGMP via the cGMP pathway (4). This leads to PKG activation (5) and results in STX4-WT phosphorylation at Ser-78 residue (6a) to ultimately allow degradation of STX4 via the proteasome. The STX4-S78A mutant however, cannot be phosphorylated (6b), preventing STX4 degradation by proteasomes. If left intact, the STX4 protein mediates the binding of A-SMase to the plasma membrane (7), resulting in tumor cell death (8).

 

Methodology & Results

The presence of M2 polarized TAMs in U373 human glioma cells were confirmed through immunostaining of the M2 subtype marker CD206 and iNOS. The presence of double positive cells illustrated the ability for M2-TAMS in glioma cells to produce NO. To investigate the effect of CDDP-induced apoptosis, human glioma cells were cocultured with M2-TAMs and then treated with CDDP in the presence of the iNOS inhibitor L-NAME. Annexin V apoptosis staining data illustrated a three-fold decrease in tumor cell death when CDDP-treated U373 glioma cells were cocultured with M2-TAMs. However, the addition of L-NAME resulted in a roughly two-fold increase in the abundance of dead tumor cells. Similar results were observed in the GL261 murine cells. This demonstrates that NO induces resistance to the apoptotic effect of CDDP as the inhibition of the NO precursor iNOS resulted in increased efficacy of the CDDP treatment. 

The NO pathway operates via activation of the cGMP pathway. This was confirmed by administration of ODQ, a guanylate cyclase inhibitor that prevents NO-dependent cGMP generation, and DETA-NO (an NO donor) to U373 cells treated with CDDP. Results indicated a roughly two-fold increase in the percentage of apoptotic cells when treated with cGMP inhibitor ODQ, illustrating that the cGMP pathway is a significant contributor to CDDP. The generation of cGMP is correlated with the inhibition of CDDP-induced apoptosis, therefore, the presence of a cGMP inhibitor (ODQ) should increase levels of apoptosis, which is reflected in the data. 

It has been previously demonstrated that acid sphingomyelinase (A-SMase) is activated by CDDP. A-SMase activation often occurs via translocation to the plasma membrane, therefore a cell surface biotinylation assay was used in U373 to confirm increased expression of A-SMase at the plasma membrane 30 minutes post-CDDP treatment. As expected, western blotting data indicated heightened expression of the enzyme when compared to A-SMase expression in U373 cells treated either with DETA-NO or 8Br-cGMP (an activator of cGMP-dependent kinases).

The final step of the pathway conferring resistance to CDDP involves the phosphorylation of Syntaxin 4 (STX4). STX4 is a membrane-bound SNARE protein. SNARE proteins form a SNARE core complex that orchestrate vesicle fusion to the plasma membrane. In tumor cells, STX4 is known to control the trafficking of A-SMase from intracellular compartments to the plasma membrane, allowing the A-SMase to carry out the intended apoptotic effect of CDDP. However, data shows that the phosphorylation of STX4 at the Ser-78 residue promotes its subsequent proteasomal degradation. 

 

Conclusion 

It has been found that NO released by M2-polarized TAMS has led to resistance against a widely used chemotherapy drug CDDP. This is achieved via the generation of cGMP and the activation of PKG in response to increased intracellular concentrations of NO. This leads to phosphorylation of the STX4 protein at Ser-78, resulting in its degradation. The decrease of the STX4 protein immobilizes A-SMase, preventing the enzyme from reaching the plasma membrane to initiate tumoral apoptosis.

As previously mentioned, the effect of NO in large quantities yields cytotoxic properties. In smaller concentrations however, NO has exhibited protective effects. The dichotomous behavior of NO on tumor biology could be a result of a myriad of factors, including the conditions of the tumor microenvironment and its origin. The generation of NO by TAMs protects tumor cells from apoptosis through the indirect inhibition of A-SMase activity. It is important to note that this action is dependent on the ability of NO to generate cGMP in tumoral cells and block the CDDP-induced, STX4-dependent translocation of A-SMase to the plasma membrane.  

The elucidation of a chemotherapeutic resistance mechanism provides an understanding of Cisplatin’s efficiency and the origin of its drug-resistant tendencies. The observed proteasome-dependent degradation of STX4 may also be relevant to cancer therapies based on proteasome inhibitors. Prevention of the proteasomal degradation mechanism would increase efficacy of many chemotherapeutic treatments. This is due to the preservation of pro-apoptotic factors which would permit the programmed cell death of various proteins, preventing the accumulation of deleterious proteins. Currently, proteasome inhibitors are approved for treating multiple myeloma, a cancer of plasma cells or cells that produce antibodies. As NO is a major signaling molecule in the immune system, the elucidation of the CDDP resistance pathway yields further insight into how NO operates and proliferates. This renders research put forth by Perrotta et al. applicable to various fields of research beyond cancer. 

 

References

  1. Dasari, S., & Tchounwou, P. B. (2014, October 5). Cisplatin in cancer therapy: molecular mechanisms of action. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4146684/.
  2. Lin1, Y., & Jianxin. (2019, July 12). Tumor-associated macrophages in tumor metastasis: biological roles and clinical therapeutic applications. Retrieved from https://jhoonline.biomedcentral.com/articles/10.1186/s13045-019-0760-3.
  3. Nitric Oxide and Cell Stress – Cell Signaling and Neuroscience: Sigma-Aldrich. (n.d.). Retrieved from https://www.sigmaaldrich.com/life-science/cell-biology/cell-biology-products.html?TablePage=9552558.
  4. XU, W., LIU, L. Z., LOIZIDOU, M., AHMED, M., & CHARLES, I. G. (n.d.). The role of nitric oxide in cancer. Retrieved from https://www.nature.com/articles/7290133.
  5. Gorelik, A., Illes, K., Heinz, L. X., Superti-Furga, G., & Nagar, B. (2016, July 20). Crystal structure of mammalian acid sphingomyelinase. Retrieved from https://www.nature.com/articles/ncomms12196.
  6. Perrotta, C., Cervia, D., Di Renzo, I., Moscheni, C., Bassi, M. T., Campana, L., … Clementi, E. (2018, May 29). Nitric Oxide Generated by Tumor-Associated Macrophages Is Responsible for Cancer Resistance to Cisplatin and Correlated With Syntaxin 4 and Acid Sphingomyelinase Inhibition. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987706/.

Recent Efforts Toward Engineering Anticancer Plant Secondary Metabolites

By Roxanna Pignolet, Biochemistry & Molecular Biology, ‘20

Author’s note: This literature review was originally written as an assignment for my 102B Writing in the Disciplines: Biological Sciences class. At the start of this quarter I was lucky enough to get involved in plant metabolic engineering research in Dr. Patrick Shih’s laboratory, which exposed me to the field of synthetic biology for the first time. I immediately became fascinated with the whole process of engineering plants to produce medically relevant compounds. Through this review I hope to inform others of these surprising and highly relevant applications of plant genetic engineering.

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