Team:William and Mary/Engineering



Engineering Success



We followed the engineering cycle for countless iterations over the course of our project. For clarity, we have condensed the iterations and separated our experience into the steps:

  1. Research
  2. Imagine and Design
  3. Build and Test
  4. Learn and Improve
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Research


Table of Contents

  1. Overview
  2. Defense against Enveloped Viruses
  3. Defense against Positive Strand RNA Viruses
  4. Other Protective Strategies
  5. Effects on Inflammation: A Cautionary Tale
  6. PUFA Production by Microorganisms
  7. Host-Pathogen Interactions and Cytokine-Sensing by Microorganisms
  8. Commensal Bacteria Within the Nasopharyngeal Microbiome

1. Overview

Before designing our nasal probiotic, we conducted a thorough literature review on the nasal microbiome and on the capability of polyunsaturated fatty acids (PUFAs) to regulate inflammation and suppress viral replication. Research has demonstrated the antiviral effects of PUFAs against both enveloped viruses and positive, single-strand viruses (SARS CoV-2 happens to be both). Enveloped viruses utilize host lipids to form their membranes, while positive, single-strand viruses rearrange host lipids to facilitate their replication. Unsurprisingly, lipids also play a major role in the clearance of these viruses by the human immune system.

Summary of Antiviral Effects of PUFAs

Furthermore, lipids including PUFAs play a critical role in regulating inflammation through their metabolites. Prior to designing genetic circuits, we carefully considered the pro- and anti-inflammatory effects of PUFAs, consulting pulmonologist and inflammation expert Dr. James Shelhamer to better understand these effects and their implications. Additionally, we conducted extensive research on potential chasses native to the nasopharyngeal microbiome, interviewing multiple microbiology experts and medical doctors to investigate safety concerns.

Finally, we scoured the literature for genes that would allow TheraPUFA to sense inflammation and synthesize PUFA and export PUFA. Our research spanned a variety of bacterial and protist PUFA synthase complexes, as well as bacterial cytokine sensors.

The findings of our literature review are summarized below.

2. Defense Against Enveloped Viruses

The polyunsaturated fatty acids linoleic acid (LA) and arachidonic acid (AA) can inactivate enveloped viruses such as herpes and influenza by causing their membranes to leak or lyse (Kohn, Gitelman, & Inbar, Arch Virol., 1980; Das, Arch. Med. Res., 2020a; Das, Arch. Med. Res., 2020b).

3. Defense Against Positive Strand RNA Viruses

AA, as well as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), may also suppress replication of +RNA viruses (Yan et al., Viruses, 2019; Yan et al., Int. J. Mol. Sci., 2019). +RNA viruses such as coronaviruses and enteroviruses, which include polioviruses and rhinoviruses, cause significant perturbations to the lipid profile of cells. Exogenous supplementation of PUFAs may disrupt the precise lipid "homeostatic state" required by these viruses for membrane rearrangement and replication (Yan et al., Int. J. Mol. Sci., 2019).

Though not a lipid, the protein CC10 also inhibits viral replication through the suppression of membrane rearrangement. CC10 inhibits phospholipase cPLA2, which hydrolyzes membrane phospholipids to provide the lysophospholipids and free fatty acids necessary for membrane rearrangement. The potential of cPLA2 inhibitors as antivirals has been demonstrated in vitro in cells infected with coronaviruses, where chemical inhibitors successfully reduced viral replication and prevented the formation of double membrane vesicles (a type of membrane rearrangement) (Muller et al., J. Virol, 2018). In vivo, CC10 supplementation encouraged positive outcomes among rats infected with respiratory syncytial virus (Yu et al., Internal Immunopharmacology, 2020). PUFAs DHA and EPA may also inhibit cPLA2, though studies are conflicting (Vincentini et al., Clinical Nutrition, 2011; Tajuddin et al., Plos one, 2014; Shikano, Masuzawa, & Yazawa, J. Immunol., 1993; Kishida et al., BBA, 1998; Su, Neuro-Signals, 2009, Su et al., Prog. Neuro-Psychopharmacol. Biol. Psychiatry, 2018; Liu et al., Immunology, 2014).

For further clarification on the interaction between DHA and cPLA2, we consulted James Shelhamer, M.D. Dr. Shelhamer explained that lipid immune mediators are complex, and different reactions can occur depending on cell type. He also cautioned that excess cPLA2 inhibition could dampen the immune response by suppressing the recruitment of neutrophils.

4. Other Protective Strategies

Some studies suggest that bioactive lipids alter the cell membrane and its fluidity such that viral proteins lose affinity for their receptors (ex: SARS CoV-2 spike protein and ACE2) (Das, Arch. Med. Res, 2020b). As well, PUFAs such as EPA and DHA have a variety of general anti-inflammatory effects, both receptor-mediated (relaxation of respiratory muscle in COPD and asthma patients via receptor FFA4) and non-receptor-mediated (accumulation of EPA and DHA in membranes results in anti- rather than pro-inflammatory metabolites) (Prihandoko, bioRxiv preprint, 2020; Norris & Dennis, PNAS, 2014; Chanda et al., J. Zhejiang Univ., 2014). Such anti-inflammatory effects may protect patients against viral infections, especially those infections associated with inappropriate immune responses (cytokine storms).

5. Effects on Inflammation: A Cautionary Tale

While the utilization of PUFAs such as AA, EPA, and DHA to inhibit viruses is an appealing strategy, PUFAs are thoroughly integrated with the human immune response. AA is generally considered pro-inflammatory, whereas EPA and DHA have been shown to provide a wealth of anti-inflammatory effects. Inappropriate usage of these PUFAs could cause excess inflammation or could suppress the immune system to the point that it cannot properly defend itself against infection. For example, the usage of EPA or DHA to treat influenza in mice suppressed the immune system and stifled viral clearance (Zabetakis et al., Nutrients, 2020). As well, knockout of cPLA2 in mice (which suppresses the release of AA), hindered neutrophils from clearing bacterial infections (Hurley & McCormick, Infection & Immunity, 2008). When designing our circuit, we carefully considered the balance between PUFAs with pro- and anti-inflammatory metabolites.

6. PUFA Production and Export by Microorganisms

After selecting AA and DHA as the PUFAs for our probiotic to produce, we identified PUFA synthase enzyme complexes endogenous to bacteria and protists. In contrast to enzymes that simply elongate and desaturate existing fatty acids, PUFA synthases accomplish de novo synthesis from starting substrates malonyl and acetyl via a polyketide synthesis pathway.

Unfortunately, PUFA synthases derived from marine bacteria often demonstrate an extreme temperature sensitivity that precludes their use in a probiotic. Since these PUFA synthases adapt bacteria to colder environments, PUFA accumulation is typically not observed past 20C (Yoshida et al., Marine Drugs, 2016; Amiri-Jami et al., FEMS Microbiology Letters, 2015). The regulation of temperature-sensitivity was unclear, so we returned to our research and identified organisms that produce PUFA in warmer environments. We identified a PUFA synthase from the protist Schizochytrium which results in DHA accumulation at higher temperatures, even when expressed heterologously in E. coli (Yoshida et al., Marine Drugs, 2016, Metz et al., Plant Physiol. Biochem, 2009). For the production of AA, we identified an AA-producing PUFA synthase from Aurespira marina, a bacterium isolated from the coast of Thailand (Hosoya, Int. J. Syst. Evol. Microbiol., 2006; Ujihara et al., FEBS Letters, 2014).

After choosing suitable PUFA synthases, we searched the literature for strategies of PUFA export. Unfortunately, we did not find any articles describing the export of PUFAs following their synthesis in a bacterial cell. Therefore, we adapted strategies for long-chain fatty acids (LCFA), both saturated and monounsaturated (Tong et al., Microb. Cell Fact., 2019). We also considered repurposing the FarE protein from S. aureus, which effluxes free linoleic and arachidonic acids (Alnaseri et al., J. Bacteriol., 2015; Alnaseri et al., J. Bacteriol., 2019). For more information on the offloading of PUFAs from PUFA synthases as free fatty acids, as well as information on the export of LCFAs, we contacted Dr. Tohru Dairi and Dr. Jeong Lee (Hayashi et al., ACS Chemical Biology, 2020; Tong et al., Microb. Cell Fact., 2019). Throughout the design process, we consulted Dr. Mark Forsyth, a microbiologist at our university. Please visit our Design page for more detailed information on the genetic parts we have selected and how we propose to engineer them.

7. Host-Pathogen Interactions and Cytokine-Sensing by Microorganisms

A thorough literature review on human cytokine sensors led to the finding that human cytokine receptors naturally exist in bacteria. Pathogenic bacteria, including Aggregatibacter actinomycetemcomitans, Yersinia pestis, Neisseria meningitidis, uropathogenic E. coli, and Pseudomonas aeruginosa, S. aureus, M. avium, and M. tuberculosis naturally have receptors for human cytokines that play a role in protecting them from the immune response (Paino et al., 2012, Zav'yalov et al., 1995, Luo et al., 1993, Wu et al., 2005, Laughlin et al., Ahlstrand et al., 2017, Denis, 1992, Denis and Gregg, 1990, Gutierrez et al., 2019, Kanangat et al., 2007, Krupa et al., 2015, Mahdavi et al., 2013, Moriel et al., 2016, Paino et al., 2011, Shiratsuchi et al., 1991, Sugawara et al., 2006). However, the majority of the signaling pathways for these receptors are not well-characterized, and for some of them, binding to a cytokine does not lead to the activation of transcription. For example, OprF is an outer membrane porin from P. aeruginosa that can take two conformations: one in which it has 4 extracellular loops and another in which it has 8 extracellular loops (Sugawara et al., 2006). It was found to be specific to interferon gamma (IFN-γ) when tested against several other cytokines (Wu et al., 2005). Binding of IFN-γ to the extracellular loops causes expression of virulence factors type-I lectin and siderophore pyocyanin (Wu et al., 2005). However, the signalling pathway activated by OprF appears to be unknown.

Researchers Aurand and March were able to use OprF to create synthetic chimeric sensors for human cytokines IFN-γ and TNF-α by replacing loops from OmpA, an outer membrane porin naturally found in E. coli, with those from OprF (Aurand and March, 2015). OmpA functions with the phage shock protein system to activate transcription of specific genes. Under stressful conditions, the stress from the outer membrane protein is transduced to inner membrane proteins PspB and PspC, causing these proteins to stop interacting (Manganelli and Gennaro, 2017). When they are no longer interacting, it makes it possible for protein PspA to bind to PspC, preventing PspA from inhibiting protein PspF, as it does under non-stressful conditions (Manganelli and Gennaro, 2017). This allows PspF to activate the PspA promoter (Manganelli and Gennaro, 2017). In this way, although the signaling pathway for OprF is unknown, researchers Aurand and March were able to create a chimeric protein that uses the phage shock protein system to activate transcription of a gene of interest as a result of sensing a particular concentration of cytokines (Aurand and March, 2015). To learn more about how we plan to incorporate this sensor into our project, please visit our design page.

8. Commensal Bacteria within the Nasopharyngeal Microbiome




The nasal microbiome is highly diverse among people in both bacterial species present and relative abundance of these species (Liu et al., 2015). According to researchers Liu et al., Corynebacterium spp. (BSL1) exist in 88.2% people among the test subjects and Staphylococcus epidermidis (BSL1) exists in 90.4% people among test subjects, and Propionibacterium acnes (BSL1) exists in 83.7% of the test subjects (2015). Some species native to the nasopharyngeal microbiome are opportunistic pathogens that can cause infections, such as Pseudomonas aeruginosa (BSL2) and Staphylococcus aureus (BSL2). However, many non-infectious bacteria with potential for probiotic use also inhabit this microbiome. Promising commensal species include Corynebacterium spp. and Lactobacillus spp..

Recent research suggests that commensal bacteria can have a positive effect on host health. According to Kim et al., Staphylococcus epidermidis can increase the IFN-γ production upon influenza A virus infection from around 600pg/mL to around 1300pg/mL, which eventually leads to a suppression of viral infection (2019). This increase in IFN-γ level can also help with the cytokine sensor design in our project. Another piece of evidence for the positive effect of commensal bacteria on human health is the negative effect of nasal biodiversity loss. Loss of nasal biodiversity, which can occur during antibiotic treatment, for example, may lead to an increase in Gram negative bacteria, including many pathogenic species (Kumpitsch et al., 2019).

Antibiotics are but one factor that may shape the nasal microbiome. Though the density of nasal bacteria is correlated with host genetics, the composition of the nasal microbiome is not (Liu et al., 2015). The composition of the nasal microbiome can change depending on the host's age. In infants, one or two species among Moraxella, Staphylococcus, Streptococcus, Haemophilus, Dolosigranulum, and Corynebacterium exist in nasopharyngeal microbiome at high density (Kumpitsch et al., 2019). In adults, nasal bacteria decrease in density but increase in diversity, which is illustrated above. The nasal community of elderly individuals decreases in diversity and shifts towards a more oropharyngeal population. This change may occur due to immune-senescence of the elderly, which opens up new niches after loss of species diversity (Kumpitsch et al., 2019).

Commensal species are of particular interest to our research team, since many of these species may be capable of responding to viral infection and to inflammation without any additional engineering. For example, nasal commensal Staphylococcus epidermidis can enhance immunity against influenza A virus(Kim et al., 2019), and Pseudomonas aeruginosa can detect inflammation caused by viral infection(Wu et al., 2005). The ability of bacteria to interact with the immune system and sense cytokines can be engineered and repurposed for therapeutic purposes.

Both engineered and non-engineered nasal flora may provide a therapeutic effect when introduced in humans. Previous studies have demonstrated that Lactococcus lactis can be engineered to be administered as a probiotic nasal wash to inhibit the growth of nasal opportunistic pathogen Pseudomonas aeruginosa (Cho et al., 2020). In De Boeck et al., 2020 study, a strain of Lactobacillus casei AMBR 2 was developed as a nasal probiotic that has strong adherence to epithelial cells using its fimbriae, and can inhibit growth of several upper respiratory tract pathogens including Staphylococcus aureus, Haemophilus influenzae, and Moraxella catarrhalis. They have conducted a small trial to examine its safety. Sprayed powder of Lactobacillus casei AMBR 2 strain was administered twice a day for two weeks among 20 healthy volunteers. No serious adverse effects were observed demonstrating the safety of Lactobacillus casei AMBR 2 for use as a nasopharyngeal probiotic.

Commensal Neisseria species, such as Neisseria lactamica have also been utilized as nasopharyngeal probiotics with no severe adverse side effects (Deasy et al., 2015). Therefore commensal Neisseria may constitute good candidates for use as nasopharyngeal probiotic chassis. Specifically, Neisseria cinerea appears to be an excellent candidate for a nasopharyngeal probiotic chassis. N. cinerea is found in the nasal and oral microbiota of healthy adults and children, and is considered to be a commensal member (Custodio et al., 2020). Additionally, N. cinerea is a BSL1 organism, and is neither disease-causing, nor is known to be associated with disease (Custodio et al., 2020). Moreover, it has been found that N. cinerea may actually be beneficial, as it reduces the ability of N. meningitidis to associate with epithelial cells, potentially interfering with the ability of N. meningitidis to cause disease (Custodio et al., 2020).

In addition to our literature review, when selecting the bacterial chassis for our probiotic, we consulted a subset of our stakeholders--medical doctors who would administer the proposed therapy should it ever be implemented. We chose M.D.’s with particular expertise in immune response, rhinology, and probiotics, including E.N.T.s, allergists & immunologists, and pulmonary experts. Additionally, we interviewed microbiologist Rachel Lappan, PhD, and probiotic expert Ms. Lydia Mapstone.

Our interviewees identified strains with pre-existing evidence of safety in probiotic use, such as Lactobacillus, as well as strains that they believed could be adapted for probiotic use, such as Corynebacterium spp. Additionally, they cautioned us against species associated with illness. For example, Dr. Turner warned us against the use of Corynebacteria and Neisseria, as even BSL1 strains may be associated with illness.

Regardless of the species selected, our interviewees provided us with specific tests to evaluate chassis safety, such as whole-genome searches for concerning sequences, and immunogenicity assays. Our interviewees also apprised us of the regulations TheraPUFA would be subject to as a nasal probiotic. Please visit our human practices page for more information.

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Imagine and Design


Table of Contents

  1. Circuit design

  2. Choice of Chassis and Safety Features

Through our literature review, we learned of multiple valuable antiviral properties of PUFAs, while also discovering pro- and anti-inflammatory effects that warranted additional caution. As mentioned previously, EPA and DHA may stifle viral clearance via excessive immunosuppression. The timing of AA and DHA release during viral infection thus constituted a crucial consideration in the design of TheraPUFA. The safety of TheraPUFA, including the safety of chosen chasses, comprised a second major design consideration.

Circuit Design

Inflammation can change drastically over the course of a viral infection, and can differ greatly between patients infected by the same virus. To address the dynamic and variable nature of inflammation during viral infection, we designed a “smart” probiotic capable of sensing and responding to different stages of infection and degrees of inflammation.

We have summarized TheraPUFA’s design below. For detailed information on circuit design, alternative circuits, and future directions can be found on our Design page .

TheraPUFA has two groups of bacteria that differ in the genetic circuits that they contain. One group constitutively produces and secretes low levels of AA, creating a hostile environment for invading viruses like SARS-CoV-2. AA would disrupt viral membranes and membrane rearrangement while also allowing for the necessary inflammatory response, including the recruitment of neutrophils. However, should inflammation become extreme, the second group would sense excess levels of pro-inflammatory cytokines such as IFN-γ and TNF α and release anti-inflammatory DHA in response. DHA would suppress the excess inflammation while also disrupting viral membranes and membrane rearrangement.

TheraPUFA contains four modules:
  1. Cytokine sensing module

  2. PUFA synthesis module

  3. PUFA export module

  4. Safety module, which includes two kill switches

Please visit our Design page for detailed descriptions of each module. An overview of TheraPUFA’s response to inflammation is shown below.

Case 1: Cytokine Concentrations Insufficient to Trigger High Pass Filter
  1. Concentrations of pro-inflammatory cytokines IFN-γ and TNF-α are beneath the detection threshold of a cytokine sensor expressed by both Bacterium 1 and 2. The low sensitivity of this sensor allows it to act as a high pass filter, responding only once cytokine concentrations have surpassed a threshold.

  2. Bacterium 1 constitutively produces arachidonic acid (AA) utilizing an Anderson series promoter J23. AA, a polyunsaturated fatty acid (PUFA) with both pro- and anti-inflammatory metabolites, leases viral envelopes and suppresses replication by positive-strand RNA viruses. AA accumulates within membrane phospholipids.

  3. Bacterium 1 secretes AA constitutively at basal levels. In the absence of the cI repressor, the uninhibited pLac promoter promotes the expression of phospholipase cPLA2, which releases AA from membrane phospholipids. AA diffuses into the extracellular environment, where it can provide a therapeutic effect. Since AA contributes primarily to pro-inflammatory metabolites, secreted AA allows the immune system to mount a response to viral infection, unlike certain anti-inflammatory agents.

  4. Bacterium 2 produces docosahexaenoic acid (DHA) utilizing a constitutive Anderson series promoter. DHA accumulates within membrane phospholipids, but is not secreted in the absence of iPLA2 phospholipase. iPLA2 is not produced when the high pass filter is not triggered.

Case 2: Cytokine Concentrations Surpass Threshold of High Pass Filter
  1. In the case of extreme inflammation, high concentrations of pro-inflammatory cytokines IFN-γ and TNF-α surpass the detection threshold of the cytokine sensor contained by both Bacterium 1 and 2. The low sensitivity of this sensor allows it to act as a high pass filter, responding once cytokine concentrations have surpassed the threshold.

  2. The cytokine sensor activates the pspA promoter in Bacterium 1, which promotes the expression of repressor cI. cI represses the pLac promoter, halting the secretion of AA. The secretion of AA, which has primarily pro-inflammatory cytokines, is turned “off.”

  3. Triggered by the high cytokine concentrations, the same cytokine sensor activates the pspA promoter in Bacterium 2. pspA promotes the expression of phospholipase iPLA2, which releases DHA from membrane phospholipids. The secretion of DHA is turned “on.” Exported DHA provides an antiviral effect while suppressing extreme inflammation. Should pro-inflammatory cytokine concentrations fall back beneath the high pass filter’s threshold, the pspA promoter will not be activated in either bacterial type. No longer inhibited by cI, Bacterium 1 will return to secreting AA. Meanwhile, DHA secretion will halt in Bacterium 2, due to the lack of activation of the pspA promoter. The switch back to AA from DHA prevents the immunosuppression some patients experience following extreme inflammation.

For more detailed descriptions of circuits, as well as for alternative circuits and future directions, please visit our Design page. For information on obstacles we faced throughout the design process, please visit our Contribution page.

Choice of Chassis and Safety Features

After consulting our stakeholders and reviewing available literature, we identified Neisseria cinerea as a viable chassis for our probiotic. Neisseria cinerea was chosen as our candidate gram negative chassis. Neisseria cinerea is a BSL1 species of bacteria that is native to, and considered to be a commensal part of the nasopharyngeal microbiome. Additionally, it may play a role in nasal microbiome health by preventing colonization by pathogenic N. meningitidis (Custodio et al., Plos Pathogens, 2020). Moreover, nonpathogenic species of Neisseria have already been used as nasal probiotics in the literature. For instance, Neisseria lactamica Y92-1009 has been used in human clinical trials to help prevent colonization by N. meningitidis (Deasy et al., 2015). The authors found that the probiotic was well tolerated by the volunteers, with no serious side effects reported, thereby demonstrating that commensal Neisseria species can be safely used as probiotics in the nasopharyngeal microbiome (Deasy et al., 2015). The combination of BSL1 status, commensal nature, presence in the healthy microbiome, and previous use of related bacteria as nasopharyngeal probiotics make N. cinerea an excellent candidate for a nasopharyngeal probiotic.

Though we will utilize N. cinerea for all probiotic cells, half of the cells will contain the machinery to produce AA, whereas the other half will contain the machinery to produce DHA. This division will lessen the total genetic material introduced into each bacterium. To further lessen the burden of genetic material, we will incorporate the circuits into the genome of the chasses, rather than attempting to transform plasmids. Plasmids are not an option for probiotics, which have no incentive to keep plasmids in the absence of an antibiotic. Chronic administration of an antibiotic is problematic, necessitating genome-incorporation [Click here for the Genome Incorporation of Parts Protocol].

Read more on our Safety page

Lactobacillus casei is a promising gram positive chassis, with researchers even using L. casei as a nasopharyngeal probiotic in human clinical trials (De Boeck et al., 2020). After interviews with experts, including E.N.T.s, researchers, and entrepreneurs with probiotic start-ups, we learned that lactobacilli are considered very safe as they are commonly used to produce fermented foods, such as yogurt. Moreover, our interviews with medical experts highlighted that, as lactobacilli have a long history of probiotic/food consumption use, they are more likely to be approved by regulatory agencies for use as a nasopharyngeal probiotic.

However, despite that Lactobacillus is a promising probiotic chassis, one important part of our circuit design, the cytokine sensor, consists of an outer membrane chimera protein and a Psp system that detects outer membrane stress. Thus, with only one membrane, Gram positive Lactobacillus is not compatible with our circuit design. Our future works would focus on adapting TheraPUFA’s genetic circuit to Gram positive bacteria. We are currently considering editing the Gram positive Two-Component Signal Transduction system. The system consists of a histidine kinase and a response regulator. The histidine kinase consists of a kinase part and a receptor part, which activate its kinase activity when the receptor binds to certain substrates (Ma et al., 2017). The response regulator will then eventually activate gene expression. Researchers have successfully replaced the sensor part of histidine kinase with a light-sensing protein, which gives bacteria the ability to produce GFP in the presence of light (Ma et al., 2017). It is possible to replace the sensor part of histidine kinase to the IFN-γ/TNF-α binding in OprF (Aurand and March, 2015) and design a Gram positive cytokine sensor.

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Build and Test


Table of Contents

  1. Overview

  2. Obtaining Parts

  3. Constructing Circuits

  4. Replicating PUFA Production Research

  5. Testing Export Systems
    1. Directing Fatty Acids to Phospholipid Synthesis: AA

    2. Directing Fatty Acids to Phospholipid Synthesis: DHA

    3. Periplasmic Localization of Phospholipases

    4. Testing Overall Export Circuit

  6. Testing Alternative Export Systems

    1. Phospholipid-Based System for PUFA Export in Gram Positive Bacteria
      • Directing Fatty Acids to Phospholipid Synthesis in Gram Positive Bacteria

      • Localization to the Gram Positive Periplasm

      • Testing Overall Export Circuit

    2. Efflux Pump-Based System for AA Export in Gram Positive Bacteria
      • Testing the Capability of FarE to Efflux AA

      • Reducing Competition between FarE and Phospholipid Synthesis

      • Testing Overall Export Circuit

  7. Testing Cytokine Sensor

  8. Testing Overall Circuit

1. Overview

We aimed to determine the feasibility of TheraPUFA as an antiviral therapy. To accomplish this, we modeled the synthesis and export of PUFAs, as well as their interaction with viral particles and human cells. Engineering and implementation of the probiotic was beyond the scope of our project. Furthermore, the COVID-19 pandemic precluded us from accessing our lab and conducting wetlab experiments.

Utilizing our novel model, we optimized parameters such as PUFA production rate, and demonstrated the feasibility of TheraPUFA as an antiviral drug. To learn about our models, please visit our Modeling page.

Though we could not access our lab this year, we have thoroughly considered how researchers could build and test our circuits.

2. Obtaining Parts

We would request plasmids from researchers Metz et al. to obtain the Schizochytrium genes necessary for DHA production (Plant Physiol. Biochem., 2009). These plasmids place the genes under the control of IPTG-induction, and include a phosphopantetheinyl transferase (PPTase) necessary for heterologous production of DHA in bacteria. If we are unable to abstain these plasmids, we could PCR the correct genetic parts from the Schizochytrium and Nostoc genomes (strains available via ATCC), or synthesize parts using services such as IDT. Similarly, to obtain the genes necessary for the AA PUFA synthase, we could request plasmids, PCR off of the Aurespira marina genome (although this particular species may be difficult to find), or synthesize parts.

3. Constructing Circuits

To assemble genetic circuits, we will utilize 3G Assembly, a hybrid Golden Gate and Gibson assembly method pioneered by Halleran, Swaminathan, & Murray (ACS Synthetic Biology, 2018). 3G Assembly begins with a Golden Gate Assembly, a type IIS assembly method utilized for the construction of “transcriptional units.” Transcriptional units contain all the genetic parts necessary for the expression of a gene, including promoter, ribosome binding site, coding sequence, and terminator. Prior to Golden Gate Assembly, each of these parts must be amplified via PCR with primers that add BsaI recognition sites. During Golden Gate Assembly, BsaI cuts outside of its recognition sites, creating sticky ends on both sides of each genetic part. These sticky ends ensure that genetic parts come together in the correct sequence to create a transcriptional unit flanked by universal nucleotide sequences (UNS). A transcriptional unit is shown below.

UNS serve as the overlap necessary for Gibson assembly, which accomplishes the insertion of one or more transcriptional units into a plasmid backbone. Successfully assembled plasmids can be transformed into E. coli and miniprepped. The complete 3G Assembly process is shown below.


Plasmids may be cloned and transformed into bacteria for preliminary testing, such as testing of individual parts of the overall circuitry. However, to test the circuits in their entirety, we will incorporate circuits into the genome of our chassis. TheraPUFA comprises much genetic material that would result in large plasmids. Additionally, plasmid use within a probiotic is not feasible. Plasmids can be maintained within bacteria via antibiotic resistance genes; however, this would require chronic antibiotic administration to a patient. As an alternative to plasmid use, we will incorporate finalized circuits into the genome of our chassis.

4. Replicating PUFA Production Research

Prior to engineering our designs, we would begin by replicating research that accomplished heterologous expression of AA and DHA PUFA synthases in E. coli. In addition to simply replicating these experiments, we could quantify the results using metrics not included in the original research. For example, AA and DHA were quantified as proportions of cellular fatty acid or membrane phospholipid. An additional metric we aim to obtain is mg/g dry cell weight, which would more easily interface with our models (models simulate nanomoles/cell). Furthermore, we will quantify extracellular PUFA in addition to centrifuging cells and quantifying cellular PUFA. In contrast with previous studies, we aim to explore the possibility that some PUFA may leave the cell and enter the extracellular environment, without the need for any engineered export mechanism (meaning the PUFA is exported via endogenous machinery such as Tol-C).

After replicating heterologous PUFA synthase expression in E. coli, we will replicate expression in our chosen probiotic chasses. Should these chassis yield no detectable PUFA, we would need to consider additional parts. For example, Hauvermale et al. showed that a phosphopantetheinyl transferase was necessary for heterologous DHA production in E. coli (Lipids, 2006). Since our chasses differ from the species of origin for the PUFA synthases, they may similarly require additional parts. Should the chasses continue to fail to produce DHA, we must pursue alternative chasses.

5. Testing Export Systems

Once we have successfully produced PUFA in E. coli and in our probiotic chassis, and quantified PUFA exported via endogenous mechanisms, we will build and test systems for optimized export.

5.1 - Directing Fatty Acids for Phospholipid Synthesis: AA

TheraPUFA exports PUFAs by first incorporating them into the plasma membrane, then releasing them from membrane phospholipids using a phospholipase localized to the periplasm. Whereas DHA has been observed to accumulate intracellularly as free fatty acid, E. coli successfully incorporates heterologously-synthesized AA into membrane phospholipids (Metz et al., Plant Physiol. Biochem., 2009; Ujihara et al., FEBS Letters, 2014). It is possible that our chosen probiotic chasses can also successfully incorporate AA into membrane phospholipids, without the need for additional engineering. To investigate this possibility, we will quantify PUFA incorporated within different phospholipids as described in the protocol at the bottom of the page. Additionally, we will determine the position of AA in phospholipids as described in Beerman et al., (Lipids, 2005). Endogenous enzymes (PlsB or C for E. coli, PlsX,Y, or C for other gram negative species) differ in the position at which they insert phospholipids (Sohlenkamp & Geiger, FEMS Microbiology Reviews, 2016). Determining the position of AA in membrane phospholipids is critical for our choice of phospholipase, since phospholipases typically demonstrate a preference for either position. Typically, PUFAs are inserted at the sn-2 position.

If endogenous mechanisms cannot incorporate AA into membrane phospholipids in sufficient quantities, we will heterologously express an acyl-CoA ligase (also called an acyl-CoA synthetase) to activate free AA such that it may be incorporated into membrane phospholipids. We have selected lacsA, an acyl-CoA synthetase from diatom Thalassiosira pseudonana which has a preference for PUFA (Tonon et al., Plant Physiology, 2005). We can quantify activated acyl-CoA in the cell, as well as quantify the proportion of fatty acids present in different membrane phospholipids.

An initial experiment will quantify activated intracellular PUFA-CoA to simply indicate whether free fatty acid produced by the cell is successfully activated. If this experiment suggests intracellular PUFA activation has been accomplished, we will conduct a phospholipid composition assay on cells with the synthetase and cells without it. Comparing phospholipid compositions between the two strains will indicate whether activation by the synthetase diverts fatty acid into the phospholipid synthesis pathway. For example, if cells with the synthetase contain AA within phospholipids while cells lacking the synthetase only contain AA as intracellular free fatty acid, this result would indicate that activation by the synthetase makes fatty acids available for phospholipid synthesis.

5.2 - Directing Fatty Acids to Phospholipid Synthesis: DHA

As described previously, TheraPUFA exports PUFAs by first incorporating them into the plasma membrane, then releasing them from membrane phospholipids using a phospholipase localized to the periplasm. We will utilize the T. pseudonana acyl-CoA ligase to activate free DHA such that it may be incorporated into membrane phospholipids. This ligase is necessary in the case of DHA, which accumulates as a free fatty acid when produced heterologously in E. coli. The researchers who observed this accumulation suggested that future studies investigate acyl-CoA synthetases to activate the free DHA. We will test the efficiency of DHA activation and incorporation into phospholipids as described for AA.

5.3 - Periplasmic Localization of Phospholipases



In gram negative bacteria, the periplasm is bound by the inner and outer cell membranes. Localization to this region requires a periplasmic localization tag; we plan to utilize a cycA signal peptide from Neisseria for localization to the periplasm of Neisseria cinerea (Turner et al., The Biochemical Journal, 2005). This tag resembles the cycA’ tag utilized in Tong et al., a study which successfully localized about 90% of synthesized phospholipase to the periplasm of Rhodobacter sphaeroides (Microb. Cell Fact., 2019). To determine whether phospholipase has been effectively localized within the periplasm, we would compare cellular versus periplasmic phospholipase quantities and activities. If we observe insufficient localization or phospholipase activity, we would attempt different localization tags [Click here for the Periplasmic Protein Quantification in Gram Negative Bacteria Protocol].

5.4 - Testing Overall Export Circuit

To assess the effectiveness of the AA and DHA export systems, we will quantify cellular PUFA as well as PUFA in the extracellular media (the supernatant separated from the supernatant following centrifugation of culture media) for both strains containing the export system and strains containing the PUFA synthase but not the export system. Comparing cellular versus extracellular PUFA concentrations, as well as comparing concentrations between strains with and without the export system, will allow us to determine the effectiveness of the export system.

6. Testing Alternative Export Systems

As described on our Design page , we developed alternative circuits for the export of PUFAs. These circuits are adapted to a gram positive chassis, since 1) the lack of an outer membrane may optimize export efficiency and 2) gram positive species such as Lactobacillus have been safely utilized in nasal probiotics before, and were recommended to us by the microbiology experts and medical doctors that we consulted.

An overview of all synthesis and export systems investigated is shown above. The plus and minus symbols refer to usage in either a gram positive or negative chassis. For more information on our designed synthesis and export circuits, including all alternative circuits, please visit our Design page.

6.1 - Phospholipase-Based System for PUFA Export in Gram Positive Bacteria:

Diverting Fatty Acid to Phospholipid Synthesis in Gram Positive Bacteria

To divert fatty acid into phospholipid synthesis in a gram positive chassis, the acyl-CoA ligase discussed previously may not be used. This is due to the differences in the way that gram negative and gram positive cells construct membrane phospholipids. While both gram negative and gram positive cells contain a PlsC enzyme, the PlsC enzyme of gram negative cells can utilize acyl-CoA whereas the PlsC enzyme of gram positive cells utilizes acyl-ACP (Lu et al., Molecular Cell, 2006). This means that activating free DHA in a gram positive cell may not direct the DHA to phospholipid synthesis, since the DHA-CoA would not be available for use by enzymes like PlsC.

To direct PUFA to phospholipids in a gram positive cell, we will introduce a fatty acid kinase with specificity for PUFA, known as FakB3 from S. pneumoniae (Gullet et al., J. Biol. Chem., 2019). After phosphorylation by FakB3, DHA-PO4 can be utilized by the PlsY enzyme (which acts upon acyl-PO4). The PlsY enzyme incorporates acyl-PO4 into membrane phospholipids at the sn-1 position. Therefore, release from the membrane would require a phospholipase with a preference for the sn-1 position. To test the functionality of FakB3, we can utilize the assay described in Gullet et al. (J. Biol. Chem., 2019). After ascertaining the ability of FakB3 to phosphorylate free PUFA, we will assay phospholipids in cells containing FakB3 and cells lacking FakB3. This experiment would indicate whether phosphorylation by FakB3 has successfully directed free DHA for use in phospholipids.

Localization to the Gram Positive Periplasm

In gram positive cells, which lack an outer membrane, the inner membrane separates the periplasm from the cytoplasm, and the thick peptidoglycan cell wall separates the periplasm from the periplasm from the extracellular environment. Though not completely membrane-bound, the gram positive periplasm still constitutes a compartment in that it contains a profile of proteins unique from that of the cytoplasm (Merchante, Pooley, & Karamata, J. Bacteriol., 1995; Pooley, Merchant, & Karamata, Microbial Drug Resistance, 1996). The porous, negatively-charged cell wall acts as a sieve towards proteins secreted through the cell membrane into the periplasm. By preventing the passage of large, positively charged proteins, the cell wall “localizes” these proteins to the periplasm and creates an environment distinct from the cytoplasm (Desvaux, Candela, & Serror, Frontiers in Microbiology, 2018; van Wely et al., FEMS Microbiology Reviews, 2001). Localized proteins remain suspended within the periplasm, unlike proteins covalently bonded to the cell wall by sortases, or lipoproteins associated with the plasma membrane.

To ensure localization to the gram positive periplasm, we would either select a phospholipase that is large and positively charged, or engineer a phospholipase to exhibit these attributions. Chimeric proteins can be engineered to contain a positive charge (Stephenson et al., The Biochemical Journal, 2000). Additionally, chimeric proteins can be engineered by linking a phospholipase of interest to an additional protein (such as another phospholipase molecule) to increase the mass of the molecule. To quantify phospholipase localized to the gram positive periplasm, we would utilize the protocol described here [Click here for the Periplasmic Protein Quantification in a Gram Positive Bacteria Protocol].

Testing Overall Export

To assess the effectiveness of the export systems, we will quantify cellular PUFA as well as PUFA in the extracellular media (the supernatant separated from the supernatant following centrifugation of culture media) for both strains containing the export system and strains containing the PUFA synthase but not the export system. Comparing cellular versus extracellular PUFA concentrations, as well as comparing concentrations between strains with and without the export system, will allow us to determine the effectiveness of the export system.

6.2 - Efflux Pump-Based AA Export in Gram Positive Bacteria


We designed an additional export system that utilizes the free fatty acid pump FarE from S. aureus to pump out free AA. FarE is typically regulated by the FarR gene; in our circuits, FarE will be under the control of a constitutive promoter (Alnaseri et al., J. Bacteriol., 2015; Alnaseri et al., J. Bacteriol., 2019).

Testing the Capability of FarE to Efflux AA

FarE has been hypothesized to efflux both linoleic acid (LA) and AA, since it is induced by both of these fatty acids. However, its ability to extrude fatty acid has only been tested on LA (Alnaseri et al., J. Bacteriol., 2015). To test the ability of FarE to efflux AA, we will utilize the same protocol utilized by Alnaseri et al. to quantify LA extrusion (J. Bacteriol., 2015). Since S. aureus lacks a beta-oxidation pathway, it must either incorporate AA within membrane phospholipids or efflux it. If FarE can efflux AA, we would expect engineered S. aureus to have a lower level of membrane-incorporated AA than knockout strains, similar to the results for LA in Alnaseri et al. (J. Bacteriol., 2015).

Reducing Competition between FarE and Phospholipid Synthesis

If FarE can extrude AA as it is hypothesized to extrude LA, we can implement it in our chosen gram positive chassis to extrude AA produced by the Aurespira marina PUFA synthase. As mentioned previously, endogenous enzymes may be capable of incorporating AA into membrane phospholipids without the need for additional engineering. If endogenous enzymes are indeed capable, as quantified by phospholipid composition assays described in Ujihara et al. (2014), then they will reduce the amount of free AA available for efflux by FarE. To counteract this, we may introduce an intracellularly-expressed phospholipase to release free AA back into the cytoplasm. We can then quantify free AA in cells lacking the phospholipase and cells which contain it [Click here for the PUFA differentiation and quantification protocol].

Testing Overall Export

To assess the effectiveness of the AA export systems, we will quantify cellular AA as well as AA in the extracellular media (the supernatant separated from the supernatant following centrifugation of culture media) for both strains containing the export system and strains containing the AA synthase but not the export system. Comparing cellular versus extracellular AA concentrations, as well as comparing concentrations between strains with and without the export system, will allow us to determine the effectiveness of the export system.

7. Testing Cytokine Sensor

The first step in testing the synthetic sensors designed by researchers Aurand and March would be to replicate their experiments in which they tested the sensitivity of their sensors to cytokines IFN-γ and TNF-α separately (Aurand and March). In order to do this, we would first engineer a BSL-1 strain of E. coli with a plasmid containing genes that encode the chimeric cytokine sensor along with a modified pBAC-LacZ plasmid that contains the PspA promoter in place of the LacZ promoter. As the phage shock protein system is native to E. coli, we would not need to engineer it to express this system. Then, using the protocol that researchers Aurand and March used (Aurand and March), we would test PspA promoter activity by using a beta-galactosidase kinetic assay and measuring fluorescence in relative fluorescence units (RFU) (Aurand and March). We would measure RFU for binding assays with IFN-γ and TNF-α independently, as done by Aurand and March (Aurand and March). After testing this in E. coli, we would engineer our probiotic chassis to express the chimeric cytokine sensor and the phage shock protein system and replicate the experiments described above using our probiotic chassis.

The next step would be to test these sensors in the presence of both IFN-γ and TNF-α. For this step, we would again start with a BSL-1 strain of E. coli and perform a binding assay in which both TNF-α and IFN-γ would be tested simultaneously, rather than independently as before. We would again follow the methods used by Aurand and March, but modify them to test the sensors using both cytokines at once (Aurand and March). We would then conduct a b-galactosidase kinetic assay (Aurand and March) to see whether sensor activity is increased in the presence of both TNF-α and IFN-γ when compared to each independently. After testing this in E. coli, we would replicate the experiments described using our probiotic chassis.

The third step would be to test the selectivity of the sensors. Although they were tested for sensitivity, the synthetic sensors designed by Aurand and March were not tested for their selectivity for IFN-γ or TNF-α, as they were not tested for their ability to sense any other cytokines. Therefore, we would need to repeat the binding assays done by Aurand and March (testing TNF-α and IFN-γ independently) using a wide range of other cytokines. These binding assays would each be followed by a set of b-galactosidase kinetic assays to measure sensor activity. Again, experiments done using E. coli would be replicated using our probiotic chassis. Please see this link for a detailed explanation of the protocols for these experiments [Click here for the Testing of Cytokine Sensor Protocol].

8. Testing Overall Circuit

In order to test our overall circuit, we will need to assess the ability of AA and DHA to decrease viral load along with the ability of the probiotic’s AA-producing strain and the probiotic’s DHA-producing strain to decrease viral load. To assess this, we would perform plaque assays using Vero E6 cells, which have been found to be the most effective for SARS-CoV-2 quantification due to their high rate of infectivity (Harcourt et al., 2020). However, the Vero E6 cells would be infected with a BSL1 strain of coronavirus (as we do not have BSL3 facilities at William and Mary) and viral load would be quantified through analysis of the presence of viral plaques. We would perform several trials in which the cells are exposed to AA and DHA in varying concentrations for our initial set of experiments. These would be followed by experiments testing the effect of the probiotic’s AA-producing and DHA-producing strains on viral load, again by quantifying viral load through analysis of viral plaques. Please see this link for a detailed explanation of the protocols for these experiments [Click here for the Quantifying Viral Titer Protocol].

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Learn and Improve → Research


The results of our mathematical models emphasized the effect of mucociliary clearance, probiotic dosage, frequency of probiotic replenishment, and PUFA production rate on the effectiveness of our probiotic. We varied these parameters along with seven others to determine the optimal functioning of TheraPUFA, and quantify the improvement necessary to achieve this optimal state. For example, our mathematical models demonstrated the need to greatly extend retention time of the probiotic within the nasal cavity, despite mucociliary clearance. The need to extend retention time led us to research mucoadhesive poloxamer gels, as suggested by Dr. Shikani. Without this technology, the probiotic would be swept away too quickly to provide a significant effect. Similarly, our model provided the optimal frequency of probiotic replenishment within the nasal cavity, which was greater than the frequencies suggested by medical doctors we interviewed. When replenished at insufficient frequencies, the model predicted little to no effect on viral titer. These results led us to alter our proposed implementation strategy with respect to dosage. Additionally, the model’s results implied that we would need to greatly increase PUFA production rate to achieve significant reduction of viral titer. In light of these results, we researched means to optimize PUFA production, such as by knockout out the FadE gene such that heterologously expressed PUFA synthases no longer compete significantly with endogenous fatty acid synthases for starting substrates. For more information regarding our model and designs, please visit our model and design pages.

Alongside our mathematical model, our human practices played a pivotal role in informing our designs. Through our interviews with medical professionals and probiotic and drug experts, we received guidance on design, safety considerations, regulations, and accessibility. Dr. Shelhamer’s feedback and expertise on inflammation was instrumental in our construction of the smart circuit. Alongside the other medical experts we interviewed, he also informed our choice of probiotic chassis and killswitch. Additionally, we developed our proposed implementation plan based off of the input of our interviewees, who provided their perspective on probiotic administration, regulation, accessibility. Please see our Human Practices page for more detail.

For the sake of clarity, we have described our engineering experience linearly along the categories of research, imagine & design, build & test, and learn & improve. However, our engineering experience was anything but linear, as we iterated through the engineering cycle countless times. The information we learned through literature review, human practices, and mathematical modeling led us to begin the cycle again, researching means to improve and optimize TheraPUFA.

The generic engineering cycle is shown below. Beneath it are a few examples of how we followed the engineering cycle, returning to the research phase after analyzing information we received from our mathematical model, our human practices, or from the literature.

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Docosahexaenoic 3D Conformer: PubChem Identifier: CID 445580 URL: https://pubchem.ncbi.nlm.nih.gov/compound/445580#section=3D-Conformer

Arachidonic Acid 3D Conformer: PubChem Identifier: CID 444899 URL: https://pubchem.ncbi.nlm.nih.gov/compound/444899#section=3D-Conformer