Research Imagine and Design Build and Test Learn and Improve References

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:

Research
Imagine and Design
Build and Test
Learn and Improve

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Research

Overview
Defense against Enveloped Viruses
Defense against Positive Strand RNA Viruses
Other Protective Strategies
Effects on Inflammation: A Cautionary Tale
PUFA Production by Microorganisms
Host-Pathogen Interactions and Cytokine-Sensing by Microorganisms
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

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:

Cytokine sensing module
PUFA synthesis module
PUFA export module
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

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.
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.
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.
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

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.
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.”
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.

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Genome Incorporation of Parts Protocol

The following is a method known as CRISPR/cas9-coupled lambda Red recombineering, which was applied by Xia et al. to express fatty acid metabolic genes from Shewanella within E. coli’s genome. This is similar to what we would do by integrating several foreign genes involved in the production and export of PUFA within the genome of our probiotic candidate, Neisseria Cinerea.

Part A: Making electrocompetent cells and transforming with linear DNA

Materials

Purified PCR product with 50 bases of flanking homology or oligonucleotide primers with 35 bases of flanking homology on either side of desired change.
Bacterial strain expressing defective lambdoid prophage recombination system ƛ Red LB medium and plates (prophage can be moved in by transduction).
Medium lacking carbon source: M9 medium or 1 x TM buffer.
Selective plates: minimal plates for selecting for prototrophy.

Procedure

Design and procure the oligonucleotides for PCR-mediated generation of a dsDNA product. This product will consist of all donor genes to be incorporated in the bacterial genome.
Make the PCR product and examine it by agarose gel electrophoresis. The product has now been amplified and verified to be as it was designed.
Clean PCR product by ethanol precipitation to remove salt.
Inoculate a suitable strain of Neisseria cinerea from frozen stock or single colony into 3-5 ml LB medium. N. cinerea is our probiotic chassis, so we are preparing it to accept the new genes. Shake the culture overnight at 30-32 C.
Add 0.5 ml of the overnight culture to 35 ml LB medium in 250 ml Erlenmeyer flask.
Place flask in 32 C shaking water bath and grow cells for 2 hr.
Transfer half the culture to a 125 ml Erlenmeyer flask in 42 C water bath. Shake 15 min at 220 rpm to induce recombination. Leave the remainder of the culture at 32 C, to be used as the uninduced control.
Rapidly cool flask in ice water with gentle swirling. Leave on ice for 5 minutes. Cool the uninduced culture the same way.
Transfer both cultures to chilled 35-50 ml centrifuge tubes. Centrifuge for 7 min at 4600 x g (6700 rpm) and 4 C. Pour off supernatant.
Add 1 ml ice cold distilled water to the cell pellets and resuspend cells with a large pipet tip. Add an additional 30 ml ice-cold distilled water to each tube. Seal tube and gently invert to mix. Centrifuge tubes again.
Decant the supernatant carefully and suspend each pellet in 1 ml ice cold distilled water.
Transfer suspended cells to 1.5 ml microcentrifuge tubes. 30-60 sec at maximum speed and 4 C. Aspirate supernatant carefully. Resuspend pellet in 200 µl ice cold distilled water.
Chill 0.1 cm electroporation cuvettes on ice. Set the electroporator to 1.80 kV.
In microcentrifuge tubes on ice, mix 100-150 ng of PCR fragment with 50-100 µl of the cell suspensions. Rapidly mix and perform electroporation. Include controls of induced cells without DNA and uninduced cells with DNA.
Introduce DNA to cells by electroporation. The time constant should be 5 msec or greater.
Immediately after electroporation, add 1 ml LB medium to cuvette using micropipettor with 1000 µl pipet tip. While not selecting for drug resistance, it is still recommended to allow 30 min for the cells to recover from the electroporation shock in broth.
Prepare serial 1:10 dilutions of the electroporation mix through 10^-6 using M9 medium or 1 x TM buffer, dispensing 0.9 ml buffer and 0.1 ml cell suspension per tube.
Spread 100 µl of 10^-4, 10^-5, and 10^-6 dilutions on LB plates and incubate 1-2 days at 30-32 C.
To determine recombinant cell count, plate cells on selective plates. Spread both 10 and 100 µl of the 10^-1 and 10^-2 dilutions if efficient recombination is expected. For controls, plate 200 µl directly onto selective plates.
Incubate plates to the appropriate temperature of 30-32 C.
Confirm the presence of the desired mutations by PCR analysis, followed by DNA sequencing or restriction digestion analysis. The recombinant junctions should be confirmed with two flanking primers and two additional primers pointing outwards.

Part B: Selection for gene replacement (optional)

- For selectable cassette cat-sacB, use bacterial strain TUC01 (DY329 with cat-sacB insertion on E. coli chromosome)
- Hybrid primers to amplify cassettes: Primer L sacB: 5’-homology sequence-ATCAAAGGGAAAACTGTCAT-3’. Primer R cat: 5’-homology sequence-TGTGACGGAAGATCACTTCG
- For counter-selection, use LB plates lacking NaCl but containing 6% sucrose

Amplify the cat-sacB cassette from the appropriate template with the Invitrogen Platinum High Fidelity enzyme and an MJ Research thermal cycler, using 50 pmol of each primer.
Visualize the PCR product on an agarose gel. Purify the PCR product to remove salt.
Insert the cassette into the chromosome as described in steps 4-21 for part A. Test isolates for sensitivity to sucrose on LB plates lacking NaCl but containing 6% sucrose. Use a strain lacking a sacB insertion as a sucrose resistant control.
Use a confirmed candidate as the starting bacterial strain for a second round of recombineering by carrying out part A, but at step 16, suspend the electroporated cells in a final volume of 10 ml LB medium and incubate with aeration overnight at 30-32 C.
Centrifuge cells 7 min at 4600 x g and 4 C. Remove supernatant, then wash cells two times, each time suspending in 1 ml minimal medium lacking a carbon source, centrifuging again, and removing supernatant. Suspend and dilute the cells, then plate 100 µl of 10^-1, 10^-2, and 10^-3 dilutions on LB sucrose plates at 30-32 C.
Purify 12 colonies on sucrose plates by streaking to isolate single colonies.
Screen the colonies by PCR, then sequence to confirm the presence of the desired change.

Part C: Removal of the prophage (optional)

- Oligonucleotide primers for amplifying the bacterial attB site: 5’GAGGTACCAGGCGCGGTTTGATC3’ 5’GTTGCCGATGTGCGCGTACTG3’.
- E. coli K12 strain lacking the prophage (W3110), but containing attB and biotin genes.
- M63 minimal glucose plates with and without biotin.

Amplify bacterial attB site by PCR using 50 pmol of each oligonucleotide primer with E. coli K12 strain lacking the prophage as a template. The technique used is colony PCR and a fresh colony is then picked with a sterile inoculating loop and mixed into the PCR reaction.
Delete the prophage region by recombineering (Part A steps 1-18) using the attB PCR product for recombination.
Wash cells in minimal salts two times and resuspend them in the same medium for plating. Select for the desired recombinant on minimal glucose plates lacking biotin but containing vitamin B1 by incubating 4 hr at 32 C, then shifting to 42 C until colonies appear.

References

Thomason, L. C., Sawitzke, J. A., Li, X., Costantino, N., & Court, D. L. (2014). Recombineering: genetic engineering in bacteria using homologous recombination. Current protocols in molecular biology, 106, 1.16.1–1.16.39. https://doi.org/10.1002/0471142727.mb0116s106
Xia, J., Wang, L., Zhu, J., Sun, C., Zheng, M., Zheng, L., . . . Shi, L. (2016). Expression of shewanella frigidimarina fatty acid metabolic genes in E. coli by CRISPR/cas9-coupled lambda red recombineering. Biotechnology Letters, 38(1), 117-122. doi:http://dx.doi.org/10.1007/s10529-015-1956-4

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].

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Build and Test

Overview
Obtaining Parts
Constructing Circuits
Replicating PUFA Production Research
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
Testing Alternative Export Systems

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
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

Testing Cytokine Sensor
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

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Periplasmic Protein Quantification: Gram Negative Bacteria

Motivation

Determine whether phospholipases have been properly localized to the periplasm, where they can release PUFA from the inner membrane. Proper localization is essential for PUFA export.
Assess the functionality of the gram negative periplasm as a compartment for phospholipases

Objectives

Quantify phospholipase localized to the periplasm
Quantify phospholipase activity in enzyme units/mg protein, where one enzyme unit equates to 1 μmol of free fatty acids (FFA) released per min from phospholipids (PL) under examined conditions
Quantify activity within the cytoplasm and the periplasm individually. Comparing calculated activities will allow us to assess the functionality of localized phospholipase.

Reagents and Equipment

Probiotic strain (Neisseria cinerea)
Centrifuge, Sonicator
Tris-sucrose-EDTA buffer
Ice
Sodium borate buffer
CaCl2
FFA quantification colorimetric/fluorometric kit
Methyl nonadecanoate (C19:0)
Methyl tricosanoate (C23:0)

This protocol is adapted from the protocol for periplasmic fraction preparation in Production of long-chain free fatty acids from metabolically engineered Rhodobacter sphaeroides heterologously producing periplasmic phospholipase A2 in dodecane-overlaid two-phase culture by researchers Tong et al. Certain specifics have been modified to better fit our experiment. The periplasmic fraction was prepared to allow the researchers to measure the activity of the phospholipase in the periplasm which would allow them to confirm the heterologous expression and periplasmic localization of PLA2 of Rs-A2.

To prepare the periplasmic and cytoplasmic fractions:

Grow bacterial cells under optimal conditions and harvest at the exponential growth phase by centrifugation at 3000g and 4°C for 20 min.
Suspend the cell pellet in 1 mL of Tris-sucrose-EDTA (200 mM Tris–HCl, pH 8.0, 500 mM sucrose, 1 mM EDTA) buffer.
Incubate on ice for 30 minutes.
Centrifuge at 16,000g and 4°C for 30 minutes.
Recover the supernatant which constitutes the periplasmic fraction.
Suspend the pellet, which contains the spheroplasts, in 20 mM sodium borate buffer (pH 9.0).
Sonicate on ice
Centrifuge the mixture at 12,000g at 4°C for 10 minutes.
Recover the supernatant which constitutes the cytoplasmic fraction.

Measurement of Phospholipase activity:

Obtain membrane phospholipids from the probiotic cells to use as the substrate for the assay.
Prepare the reaction mixture by mixing an aliquot (35 μg protein) of the periplasmic or cytoplasmic fraction along with 400 µg of PLs (Phospholipids) in 1 mL of 20 mM sodium borate buffer (pH 9.0) containing 1 mM CaCl2.
Perform the reaction at 30°C for 15 minutes.
Terminate by heating at 100°C for 5 minutes.
Centrifuge the mixture at 12000g and 4°C for 10 min.
Examine the supernatant for FFA using the FFA quantification colorimetric/fluorometric kit. Perform the reaction without a cell fraction aliquot as a control.
Prepare a standard curve by using varying concentrations of the relevant reagent depending on the PUFA being measured. 1 mg of methyl nonadecanoate (C19:0) should be used as the internal standards for reference when measuring arachidonic acid (C20:4n6) and 1 mg of methyl tricosanoate (C23:0) should be used for docosahexaenoic acid (C22:6n3). Look at the protocol for PUFA Quantification and Differentiation for more information.
Measure phospholipase activity for both the periplasmic and cytoplasmic fractions and compare.
Phospholipase activity is measured in enzyme units “U” per mg protein, where one enzyme unit equates to 1 μmol of FFAs released per min from PLs under examined conditions.

Reference

1. Tong, X., Oh, E.K., Lee, B. et al. Production of long-chain free fatty acids from metabolically engineered Rhodobacter sphaeroides heterologously producing periplasmic phospholipase A2 in dodecane-overlaid two-phase culture. Microb Cell Fact 18, 20 (2019). https://doi.org/10.1186/s12934-019-1070-8

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

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Periplasmic Protein Quantification: Gram Positive Bacteria

Motivation

Determine whether phospholipases have been properly localized to the periplasm, where they can release PUFA from the inner membrane. Proper localization is essential for PUFA export.
Assess the functionality of the gram negative periplasm as a compartment for phospholipases

Objectives

Quantify phospholipase localized to the periplasm
Quantify phospholipase activity in enzyme units/mg protein, where one enzyme unit equates to 1 μmol of free fatty acids (FFA) released per min from phospholipids (PL) under examined conditions
Quantify activity within the cytoplasm and the periplasm individually. Comparing calculated activities will allow us to assess the functionality of localized phospholipase.

Reagents and Equipment

Probiotic cells (Lactobacillus casei)
Manifold
Incubator
Phase contrast microscope (Optional)
TLP Isotonic buffer solution (TMS); Contains Tris-Hcl, MgCl2, sucrose
Lysozyme
Phenyl-methylsulfonyl fluoride
Sodium borate buffer
CaCl₂
FFA quantification colorimetric/fluorometric kit
Methyl nonadecanoate (C19:0)
Methyl tricosanoate (C23:0)

This protocol is adapted from “A periplasm in Bacillus subtilis” by researchers Rafael Merchante, Harold M. Pooley, and Dimitri Karamata. The researchers aimed to quantitatively and qualitatively investigate the presence of the periplasm in gram positive bacteria.

Cell fractions preparation¹:

Grow cell cultures for our probiotic cells under appropriate conditions.
Extract 25 ml culture aliquots from early exponential to late stationary phase at appropriate times.
Harvest cells by filtering on a manifold, wash 4 times with 2 ml of TLP, and immediately resuspend in a 0.5 ml freshly prepared isotonic buffer solution (TMS) containing Tris-Hcl (50 mM, pH 8.0), MgCl2 (16 mM), and sucrose (66% or sometimes 33% [wt/vol]).
Add Lysozyme and (100- to 200 ug ml final concentration) and phenyl-methylsulfonyl fluoride (0.1 mM final concentration) and incubate the suspension at 37°C.
After 30 to 60 minutes, more than 99% of the cells should have been converted to protoplasts. Can use phase contrast microscopy to confirm.
Pellet the protoplasts for 15 minutes at 21,000 x g.
Collect the protoplast supernatant fraction (PSF).
You now have the PSF with soluble periplasmic proteins. The PSF might also contain cell-wall bound proteins, proteins secreted across the cell wall, and contaminating proteins from the cytoplasm or membrane during cell fractionation.
To further obtain the cytoplasm and membrane fractions, first lyse the protoplasts mentioned above by resuspending them in a lysis buffer containing Tris-HCl (50 mM, pH 8.0) and MgSO4 (5mM).
Repeatedly pass through a 1 ml micropipette tip.
Centrifuge for 1 h at 21,000 x g to allow separation of the cytoplasmic and membrane fractions.

Measurement of Phospholipase activity¹:

Obtain membrane phospholipids from the probiotic cells to use as the substrate for the assay.
Prepare the reaction mixture by mixing an aliquot (35 μg protein) of the periplasmic or cytoplasmic fraction along with 400 µg of PLs (Phospholipids) in 1 mL of 20 mM sodium borate buffer (pH 9.0) containing 1 mM CaCl2.
Perform the reaction at 30°C for 15 minutes.
Terminate by heating at 100°C for 5 minutes.
Centrifuge the mixture at 12000g and 4°C for 10 min.
Examine the supernatant for FFA using the FFA quantification colorimetric/fluorometric kit. Perform the reaction without a cell fraction aliquot as a control.
Prepare a standard curve by using varying concentrations of the relevant reagent depending on the PUFA being measured. 1 mg of methyl nonadecanoate (C19:0) should be used as the internal standards for reference when measuring arachidonic acid (C20:4n6) and 1 mg of methyl tricosanoate (C23:0) should be used for docosahexaenoic acid (C22:6n3). Look at the protocol for PUFA Quantification and DIfferentiation for more information.
Measure phospholipase activity for both the periplasmic and cytoplasmic fractions and compare.
Phospholipase activity is measured in enzyme units “U” per mg protein, where one enzyme unit equates to 1 μmol of FFAs released per min from PLs under examined conditions.

References

Merchante R, Pooley HM, Karamata D. A periplasm in Bacillus subtilis. Journal of Bacteriology. 1995 Nov;177(21):6176-6183. DOI: 10.1128/jb.177.21.6176-6183.1995.
Schreiner M. (2005). Quantification of long chain polyunsaturated fatty acids by gas chromatography. Evaluation of factors affecting accuracy. Journal of chromatography. A, 1095(1-2), 126–130. https://doi.org/10.1016/j.chroma.2005.07.104
Tong, X., Oh, E.K., Lee, B. et al. Production of long-chain free fatty acids from metabolically engineered Rhodobacter sphaeroides heterologously producing periplasmic phospholipase A2 in dodecane-overlaid two-phase culture. Microb Cell Fact 18, 20 (2019). https://doi.org/10.1186/s12934-019-1070-8

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).

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PUFA Differentiation (and Quantification) Protocol

Motivation

Assess the ability of the probiotic to successfully synthesize polyunsaturated fatty acids (PUFAs) arachidonic acid (AA) and docosahexaenoic acid (DHA)
Assess the ability of the probiotic to successfully export synthesized PUFAs, such that PUFA is available to human cells for therapeutic effect

Protocol Objectives

Differentiate between fatty acids collected, distinguishing PUFA from fatty acids of different chain lengths and degrees of unsaturation
Quantify (mg/g of dry cell) cellular and extracellular concentrations of AA and DHA to assess the export capability of the probiotic
Distinguish between PUFAs as free fatty acids, PUFAs in activated CoA forms, and PUFAs incorporated within phospholipids

Required reagents and equipment:

GC-MS
Centrifuge
1 mL n-hexane
100 μl of 2 N methanol-KOH
.08 mg Na2SO4
1.0 ml dry chloroform
Column

By integrating the curve on the graph produced by the chromatograph, the percentage of each type of PUFA produced of the total PUFA product can be determined3. To calculate the concentrations, the area of the internal standard can be divided by the amount added. Next, this value can be used to obtain the amount of PUFA produced intracellularly and extracellularly. The units of this final value can vary based on the units used in the calculation. Our team would follow a similar procedure for the extraction, sample preparation, and calculation. Using GC-MS allows our team to determine the proportion and type of fatty acid both inside and outside the bacteria, which helps us to confirm the efficiency of our probiotic.

In order to use GC-MS for our protocol, the PUFAs of interest must be extracted from the other components in cell solution using solid phase extraction, which separates compounds based on their polarity. This separation allows the PUFAs to participate in one of several possible reactions that makes them sufficiently volatile to undergo gas chromatography. While there are multiple different reactions that can be used, they all lead to the addition of a functional group, such as esters or amides, which allows for the volatility of the PUFA. The most common reaction is the FAME method, used in Asci et. al2. The fatty acid methyl ester method or FAME method converts PUFAs into fatty acid methyl esters and enables them to travel through the gas chromatograph3.

In Asci et. al, researchers used the SO-5509, 2000 method to convert the PUFAs into fatty acid methyl esters:

Add 1 ml n-hexane to 15-32 mg of the fatty acid and vortex.
Before centrifuging at 300 rpm for 2 minutes, pipette 100 μl of 2 N methanol-KOH into the mixture.
Next, combine .08 mg Na2SO4 with the original mixture and centrifuge at 10,000 rpm for 5 minutes2.

Our team could use a similar method to prepare the PUFA produced by our probiotic for gas chromatography.

In their 2019 study, Tong et. al. utilized gas chromatography-mass spectroscopy (GC-MS) to determine the quantity and type of fatty acid produced intracellularly and extracellularly by R. sphaeroides1. By collecting samples from inside the cell and outside the cell, Kultschar et al. were able to determine the different amounts and types of fatty acids produced. Our team would utilize a similar collection method to determine the proportion of polyunsaturated fatty acids or PUFA found in each location. Following collection, Tong et al. used the FAME method for preparation of their samples.

Add 3 mL of sample to 10 µg of pentadecanoic acid.
Use chloroform and methanol to extract the components of this mixture with shaking at room temperature.
Use nitrogen steam to evaporate the chloroform layer of the separation.

Our team could use the method applied in Tong et. al. to determine the types of internal and external PUFA and to measure their quantities.

To measure absolute amounts of fatty acids, the gas chromatography detector’s response should be calibrated against a known amount of standard. Odd chain length fatty acids are rare in nature, so they can be used as internal standards by adding them at the start of the analysis and subjecting them to the same extraction and derivatization procedures as the sample. Long chain polyenes such as Docosahexaenoic acid (DHA) are vulnerable to degradation during gas chromatography analysis, since their high molecular weight causes them to elute from the column late. The long exposure to high temperature along with their high unsaturation makes them liable to react with traces of oxygen or water, so there may be losses of long chain polyunsaturated fatty acids relative to other components4. For these reasons, 1 mg of methyl nonadecanoate (C19:0) is used as the internal standards for reference when measuring arachidonic acid (C20:4n6) and 1 mg of methyl tricosanoate (C23:0) is used for docosahexaenoic acid (C22:6n3)5. The mass of arachidonic acid or AA and DHA can be converted from percentages on the chromatograph to measurements in milligrams by comparing to the curves of the standards. In Amiri-Jami et. al, researchers were able to determine the quantity of fatty acids produced in mg/g dry cell6. They accomplished this task using the mass spectrometer, which provides the mass to charge ratio of a sample. Using this ratio, Amiri-Jami et. al were able to calculate the mg/g dry cell by determining the mass of the dry cell and dividing the sample’s mass by this number6.

There are two main complications that arise from our probiotic design: incorporation of the fatty acids into the phospholipid bilayer and DHA attachment to acyl-CoA. Due to the export system of our probiotic, it is possible that some of the produced PUFA will be modified into phospholipid and incorporated into the phospholipid bilayer. Ideally, our team would be able to differentiate between the amount of PUFA free in the cell and the amount incorporated into phospholipids. However, when GC-MS is used to evaluate phospholipids, the phospholipids must undergo saponification which slightly alters their structure3. However, GC-MS still allows for the amount of phospholipid incorporated into the cell membrane to be quantified3. Using GC-MS, our team should still be able to determine the proportions and types of fatty acids free extracellularly, free intracellularly, and incorporated into phospholipid. In order to solve the Acyl-CoA problem, our team would turn to the literature. In Metz et. al, researchers radiolabeled free fatty acid in the cell. When the fatty acid was bound to acyl-CoA, it lost the radioactive label7. After sample extraction, the researchers were then able to analyze the radioactivity of the samples to determine the free and incorporated DHA7. This method would enable our team to see the amount of DHA that is free in the cell to potentially lyse viral envelopes and would enable us to further determine the effectiveness of our probiotic. In order to prepare these samples for the mass spectrometer, Metz et. al followed the following procedure7.

Centrifuge 200 mL of the sample for 17 minutes at 800 rmp.
Freeze dry the centrifuge samples overnight.
Extract the lipids from the samples with 2-ml hexane (Repeat 4 times.).
Analyze the fatty acid methyl esters with spectrometer in external El mode8.

References

1. Kultschar, B., Dudley E., Wilson S., & Llewellyn, C. A. (2020) Intracellular and Extracellular Metabolites from the Cyanobacterium Chlorogloeopsis fritschii, PCC 6912, During 48 Hours of UV-B Exposure. Fatty acid methyl ester analysis of Aspergillus fumigatus isolated from fruit pulps for biodiesel production using GC-MS spectrometry. Bioengineered. 11(1) 408-415.
2. Asci, F., Aydin, B., Akkus, G.U., Unal, A., Erdogmus, S. F., Korcan, S. E., &Jahan, I., (2020) Fatty acid methyl ester analysis of Aspergillus fumigatus isolated from fruit pulps for biodiesel production using GC-MS spectrometry. Bioengineered. 408-415.
3. Fisk, H. L , West A. L. , Childs, C. E. , Burdge, G. C, & Calder, P. C. (2014). The Use of Gas Chromatography to Analyze Compositional Changes of Fatty Acids in Rat Liver Tissue during Pregnancy. Journal of Visualized Experiments. 85, e51445.
4. Scrimgeour, C. & Traynor, C. (2017). Quantifying long chain polyunsaturated fatty acids (LC-PUFA) in fish oil concentrates and algal oils choosing the correct method. Lipid Technology, 29, 71–73.
5. Schreiner M. (2005). Quantification of long chain polyunsaturated fatty acids by gas chromatography. Evaluation of factors affecting accuracy. Journal of chromatography. A, 1095(1-2), 126–130. https://doi.org/10.1016/j.chroma.2005.07.104
6. Amiri-Jami, M., Abdelhamid, A. G., Hazaa, M., Kakuda, Y., & Griffths, M. W. (2015). Recombinant production of omega-3 fatty acids by probiotic Escherichia coli Nissle 1917. Microbiology Letters.362(20).
7. Metz, J. G., Kuner, J., Rosenzweig, B., Lippmeier, J. C., Roessler, P., & Zirkle, R. (2009). Biochemical characterization of polyunsaturated fatty acid synthesis inSchizochytrium: Release of the products as free fatty acids. Plant Physiology and Biochemistry. 47. 472-478.
8. Amiri-Jami, M., & Griffiths, M. W. (2010) Recombinant production of omega-3 fatty acids in Escherichia coli using a gene cluster isolated from Shewanella baltica MAC. Journal of Applied Microbiology. 109, 1897–1905

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.

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Testing of Cytokine Sensor Protocol

Motivation

Determine whether the cytokine sensors designed have the capability to detect specific cytokines. Test sensor’s response to IFN-γ and TNF-α independently and measure sensor activity.
Determine whether the cytokine sensors designed have the ability to detect IFN-γ and TNF-α simultaneously and measure sensor activity.
Determine the capability of the cytokine sensors to induce gene expression.
Determine the specificity of the cytokine sensors by measuring sensor activity for a wide range of cytokines

Protocol Objectives

Construct plasmid with genes encoding the designed cytokine sensor.
Construct a modified pBAC-LacZ plasmid by replacing the lacZ promoter with pspA promoter.
Detect cytokine binding using an ELISA kit.
Measure the LacZ β-galactosidase activity.

Required Reagents and Equipment

E. coli strains Dh5α and JW0940 （ΔompA::kan)1(Or our probiotic chassis with phage shock protein plasmid)
P. aeruginosa PAO1 (Or other specie/strains to amplify desired gene)

This protocol is based on Wu et al., a 2005 study in which researchers tested the cytokine binding capability of OprF in Pseudomonas aeruginosa, and Aurand et al., a 2015 study in which researchers tested the ability of a OprF-OmpA synthetic receptor to regulate gene expression.

TheraPUFA is designed to sense inflammation in the surrounding environment prior to releasing DHA, an anti-inflammatory PUFA. The probiotic interprets high concentrations of pro-inflammatory cytokines IFN-γ and TNF-α as an indicator of excessive inflammation. To sense these cytokines, TheraPUFA utilizes a synthetic cytokine sensor.

To measure the effectiveness of the cytokine sensor, we need to use the Phage Shock Protein (Psp) system in E. coli. The Psp system detects outer membrane stress and ultimately transduces the signal to PspF protein which induces the transcription of other Psp genes. Here, we modify the pBAC-LacZ plasmid and replace its promoter with pspA promoter. When the cytokine sensor binds to cytokines, it induces membrane stress, which activates the transcription of lacZ gene in the plasmid. Thus, we can measure the activity of LacZ β-galactosidase to determine the effectiveness of the cytokine sensor in inducing gene expression.

The protocols below are copied from paper Aurand et al., 2015 unmodified. Bacteria preparation:

Cultivate bacterial strains with desired genes aerobically in Luria-Bertani (LB) broth at 37 or 30℃, supplement with appropriate antibiotics: chloramphenicol 12.5 μg/mL and tetracycline 10 μg/mL. In Aurand et al., 2015, the studied gene is ompA from E.coli MG1655 and oprF from P. aeruginosa PAO1.

Plasmid construction:

Amplify target genes with PCR using Q5 High Fidelity Polymerase.
Design primers for PCR such that they have a minimum -bp homology at their ends for Gibson Assembly².
In Aurand and March, 2015, researchers use Gibson Assembly Cloning Kit to replace extracellular loops of OmpA with extracellular loops of OprF. For each sensor tested, design plasmid with the gene that codes for the sensor.
Design primers for the chromosomal amplification of the pspA promoter based on E. coli MG1655 sequence from EcoCyc³.
Amplify the genomic region containing 240-bp upstream of the pspA transcriptional start site using PCR with Q5 High Fidelity Polymerase.
Construct plasmid pPALacZ1 by replacing the lacZ promoter from pBAC-LacZ plasmid with the pspA promoter using the Gibson Assembly Cloning Kit.
Transform the plasmid into chemically competent E. coli DH5α.
If we are using chassis other than E.coli, we need to design another plasmid with all the genes encoding the Psp system. Genes should include pspA, pspB, pspC, pspD, pspE and pspF.

Binding Assay:

Whole cell enzyme linked immunoassay (ELISA) is used to screen the binding of the receptor to cytokine.
Grow modified bacteria with plasmid (In Aurand and March, 2015, it is P. aeruginosa PAO1, E. coli BW25113 and E. coli JW0940) in LB broth containing chloramphenicol (12.5μg/mL) for vector maintenance at 37℃.
Dilute culture to 1:50 with fresh LB media and grow culture at 37℃ to an OD600 of 0.5-0.6.
Harvest bacteria and wash twice with PBS.
Fix washed bacteria in 3.7% paraformaldehyde for 30 minutes and wash twice with PBS.
Adjust fixed cultures to an OD600 of 0.5 with PBS.
Coat Nunc Immobilizer Amino 96 well plates with 100 μL of culture suspension and incubate overnight with gentle rocking at 4℃.
Wash plates with PBST (PBS pH 7.2, 0.05% Tween 20) which blocks nonspecific binding sites. PBST contains 5% sucrose and 1X micellar casein and blocks nonspecific binding sites for 1 hour at 37℃.
Add cytokines (In Aurand and March, 2015 study, it is 100μL IFN-γ and 100μL TNF-α) to the microtiter plate and incubate at room temperature for 1 hour. For our project, we need to test a wide range of cytokines to determine sensor selectivity. Possible cytokines for our project include IL-2, IL-4, IL-6, IL-8, IL-10, IL-12, TNF-α and IFN-γ and more.
Bound cytokine can be detected using a specific ELISA kit.

β-Galactosidase activity assay:

Culture transformed E. coli strain with pPALacZ1 plasmid and cytokine sensor plasmid in LB media supplemented with appropriate antibiotic overnight at 37℃.
Dilute culture to an OD₆₀₀. of 0.05 with fresh LB media and incubate at 30℃ until OD₆₀₀. of 0.2 prior to the addition of an inducer.
Testing of the phage shock protein system uses 5% or 10% ethanol to induce membrane stress in bacteria.
Testing of cytokine sensing uses cytokine at the concentration of 1nM. The active response range examined is 0-1000pM. For our project, we need to measure β-Galactosidase activity using IFN-γ at 1nM individually/ TNF-α at 1nM individually/ 1nM IFN-γ and 1nM TNF-αsimultaneously. To test an AND-gate, we want to see whether the result for the IFN-γ + TNF-α group is greater than the previous two. We can also use other cytokines to test their effect on gene expression.
Collect culture in 200μL aliquots, record OD₆₀₀., and freeze at -80℃ to lyse cells.
Β-galactosidase activity is measured by a kinetic assay. (Ramsay et al., 2011)
Thaw samples at 37℃, diluted 1:10 with LB media.
Dispense 10μL aliquots into black polystyrene 96 well plate.
Dispense 100μL of reaction buffer (PBS pH 7, 2mg/mL lysozyme, 0.5 mg/mL 4-methylumbelliferyl-β-D-galactopyranoside (dissolved in DMSO)) into each well.
Monitor fluorescence immediately after adding the reaction buffer. Fluorescent parameter follows: excitation 360 nm, emission 460nm, measured every minute for 30 min. Relative fluorescence units (RFU) are produced per minute for each well.
Calculate RFU/min/OD₆₀₀.

References

Baba, Tomoya, Ara, Takeshi, Hasegawa, Miki, Takai, Yuki, Okumura, Yoshiko, Baba, Miki, . . . Mori, Hirotada. (2006). Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: The Keio collection. Molecular Systems Biology, 2(1), 2006.0008-N/a.
Gibson, Daniel G, Young, Lei, Chuang, Ray-Yuan, Venter, J Craig, Hutchison, Clyde A, & Smith, Hamilton O. (2009). Enzymatic assembly of DNA molecules up to several hundred kilobases. Nature Methods, 6(5), 343-345.
Keseler, Ingrid M, Mackie, Amanda, Peralta-Gil, Martin, Santos-Zavaleta, Alberto, Gama-Castro, Socorro, Bonavides-Martínez, César, . . . Karp, Peter D. (2013). EcoCyc: Fusing model organism databases with systems biology. Nucleic Acids Research, 41(D1), D605-D612.
Joshua P. Ramsay, Neil R. Williamson, David R. Spring, & George P. C. Salmond. (2011). A quorum-sensing molecule acts as a morphogen controlling gas vesicle organelle biogenesis and adaptive flotation in an enterobacterium. Proceedings of the National Academy of Sciences - PNAS, 108(36), 14932-14937.
Wu, L., Estrada, O., Zaborina, O., Bains, M., Shen, L., Kohler, J., . . . Alverdy, J. (2005). Recognition of host immune activation by Pseudomonas aeruginosa. Science (New York, N.Y.), 309(5735), 774-777.
Aurand, T., & March, J. (2015). Development of a synthetic receptor protein for sensing inflammatory mediators interferon‐γ and tumor necrosis factor‐α. Biotechnology and Bioengineering, 113(3), 492-500.

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].

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Quantifying Viral Titer

Motivation

Assess the ability of arachidonic acid (AA) and docosahexaenoic acid (DHA) to decrease viral titer
Assess the ability of the probiotic’s AA-producing strain and the probiotic’s DHA-producing strain to decrease viral titer

Protocol Objectives

Test whether designed probiotic contributes to a decrease in viral titer

Required Reagents and Equipment

Vero E6 cells (ATCC® CRL-1586TM)
Cell maintenance medium
GibcoTM Trypsin-EDTA (0.25%), with phenol red
Infection medium
Specimens to be assayed for virus
GibcoTM DPBS, no calcium, no magnesium
Overlay diluent
Micro-Chem Plus Disinfectant Detergent
Class II biological safety cabinet 150-cm2
culture flasks
CO2 incubator
Light microscope
Falcon 50-ml conical centrifuge tubes
Countess II automated cell counter
6-well plates
2-ml microcentrifuge tubes
Vacuum source Serological pipettes, sterile: 5-ml,10-ml, 25-ml, 50-ml
Pipet-Aid
Repeat pipettor
Tips for repeat pipettor: 20-μl barrier tips, 200-μl barrier tips, 1000-μl barrier tips
44°C water bath
Timer
3% carboxymethylcellulose
10% neutral-buffered formalin
Formalex GREEN Formalin Neutralizer
0.5% crystal violet

Summary: Plaque assays will be performed utilizing Vero E6 cells, according to the second method provided in Harcourt et al. Though this method requires additional steps compared to the first method described in the study, it provides more accurate results. The assays will be utilized to determine the effects of AA and DHA at different concentrations individually on viral titer. Afterwards, the assays will be utilized to determine the effects of the AA and DHA-producing probiotic strains on viral titer.

In order to determine the effectiveness of our probiotic as a broad spectrum antiviral therapeutic, the effect of the probiotic on viral titer must be quantified. In order to determine viral titer, our team intends to utilize a plaque assay, which is the accepted “gold standard” in viral titer quantification^1,2. In a plaque assay, scientists use the presence of plaques, or zones of cellular viral damage, to determine viral amount¹. To utilize this this assay, two assumptions must be met:

The cells utilized in the experiment must be easily infected by the given virus.
The samples must not homogenate from the tissue being tested¹.

This year, our team was not able to get into the laboratory to perform actual experiments. Because our team was unable to actually perform this protocol, we wrote it to be as accurate as possible which involves using SARS-CoV-2. William and Mary does not have a biosafety level 3 laboratory. If we were to perform this protocol in actuality, we would have to either perform this protocol at a biosafety level 3 laboratory or use a proxy virus. Given the current global situation, we would most likely use a proxy virus.

Researchers Harcourt et. al identified Vero E6 cells as the most effective for SARS-COV-2 viral quantification3. Harcourt et. al performed plaque assays using both Vero E6 and Vero CCL81 cells. Afterwards, they determined that Vero E6 cells had a greater infection rate, had more easily visible plaques, and were able to be quantified a day earlier than Vero CCL81 cells3. Our team would use Vero E6 cells to perform our plaque assays for increased accuracy and decreased testing times.

Plaque assays follow a basic protocol. First, a sample of unknown viral concentrations is serially diluted and used to infect cells. These cells are then treated with an immobilizing overlay to halt additional viral infection. As these cells are incubated, plaques begin to form on the cells. After staining, these plaques can be counted and used to determine the viral titer using the equation below.

Viral Titer of SARS-CoV-2 (in PFU/ml)= (Average Number of Plaques Per Identified Virus Dilution )/(Dilution Factor × 0.1)

Mendoza et al. developed two protocols for identification of SARS-CoV-2 titer2. The first method involves a primary and secondary solid overlay. Method 1²:

Add 900 μl of infection media to microcentrifuge tubes. Next, add 100 μl of the viral sample to the first tube, vortexed it, and transferred 100 μl of it to the next tube, ending with a 10-6 dilution.
Using a 6-well plate, infect the Vero E6 cells with the serial dilutions and incubate them.
Next 3 mL of a primary solid overlay medium should be applied to each well. This overlay is made using a 1:1 dilution of overlay diluent and 2% Noble Agar.
After incubation for 2 days, microwave and add 2 mL of secondary solid overlay medium, a 1:1 dilution of 2% Noble Agar and .01% neutral red.
Using a white-light transilluminator, determine the number of plaques and determine the titer using the above equation.

The other protocol that Mendoza et. al developed differs in its use of a liquid overlay medium as opposed to a solid overlay medium. Additionally, the two protocols differ in their use of staining mechanisms: the first uses the secondary overlay medium while the second uses crystal violet. These two protocols use the same infection process.

Method 2²:

Repeat Method 1 steps 1-2.
Treat cells with 3 mL per well of the liquid overlay medium, made with a 1:1 dilution of overlay diluent and 3% carboxymethylcellulose.
After incubation for 3 days, remove the liquid overlay medium and wash the cells with DPS. Add 10% buffered formalin to the wells and incubate for 1 hour.
After removing the formalin, add 200 μl of .5% crystal violet per well and allow to incubate. Clean the cells with distilled water and blot them dry.
Determine viral titer by counting the number of plaques and using the given formula.

Both of the methods provided by Mendoza et al. allow for effective viral quantification. However, each has specific benefits and drawbacks2. Method 1 has fewer washing, fixing, and staining steps, will not distort easily if plates are disturbed, and is more cost effective. Although, plaques and cells are difficult to distinguish from one another due to the neutral red staining. Additionally, the virus is viable throughout the assay when using method 1. Method 2 deactivates the virus diminishing the potential of infection, and typically produces plaques more easily distinguishable from cells, compared to plaques from method 1. However, its liquid overlay can easily be disturbed creating streaked plaques and additional steps are required².

If our team were to perform this experiment, we would use method 2. While it may involve more steps, it has more easily distinguishable plaques leading to increased accuracy. When applying method 2 to our probiotic, samples would need to be collected from cells treated with arachidonic acid (AA), cells treated with Docosahexaenoic acid (DHA) and control cells unexposed to either acid. Once these cells underwent the plaque assay process, we could compare the viral loads and determine if AA and DHA were able to decrease the viral titer of the Vero E6 cell. We would complete three trials with the cells exposed to 50 μM, 75 μM, and 100 μM of AA prior to the calculation of the viral titer. Exposure to 50 μM of AA has been shown to decrease the viral load by roughly 50 percent4. While exposure of cells to 100 μM of AA has been proven to decrease viral load to roughly 10 percent4. By testing this range of values, we hope to find the amount of AA which is best able to decrease viral load in our experimental conditions. Additionally, we would conduct a similar experiment by exposing Vero E6 cells to 30, 40, and 50 μM of DHA. DHA has been shown to decrease viral load at a concentration of 40 μM4. However, our team plans to test a range of values to determine which operates most effectively in our system.

Grow bacteria in minimal media.
Induce AA / DHA production with varying cytokine levels (added to media).
Centrifuge culture tubes, take some culture media and add to mammalian cell culture.
Test effects on viral load (making sure to include a negative and positive control, negative is bacteria grown that don’t produce PUFAs, and positive is simple addition of AA / DHA).

References

Case, J. B., Bailey, A. L., Kim, A. S., Chen R. E., & Diamond, M. S. (2020). Growth, detection, quantification, and inactivation of SARS-CoV-2. Virology, 548, 39-48
Mendoza, E. J., Manguiat, K., Wood, H., & Drebot, M. (2020). Two detailed plaque assay protocols for the quantification of infectious SARS-CoV-2. Current Protocols in Microbiology, 57, e105. doi: 10.1002/cpmc.105
Harcourt, J., Tamin, A., Lu, X., Kamili, S., Sakthivel, S. K., Murray, J., Queen, K., Tao, Y., Paden, C. R., Zhang, J., Li, Y., Uehara, A., Wang, H., Goldsmith, C., Bullock, H. A, Wang, L., Whitaker, B., Lynch, B., Gautam, R., Schindewolf, C., Lokugamage K. G., Scharton, D., Plante, J. A., Mirchandani, D., Widen, S. G., Narayanan, K., Makino, S., Ksiazek, T. G., Plante, K. S., Weaver, S. C., Lindstrom, S., Tong, S., Menachery V. D., & Natalie J. Thornburg, N. J. (2020). Severe Acute Respiratory Syndrome Coronavirus 2 from Patient with Coronavirus Disease, United States. Emerging Infectious Diseases, 26, 6.
Yan, B., Chu, H., Yang, D., Sze, K., Lai, P., Yuan, S., Shuai, H., Wang, Y., Kao, R. Y., Chan, J. F. & Yuen, K. (2019) Characterization of the Lipidomic Profile of Human Coronavirus-Infected Cells: Implications for Lipid Metabolism Remodeling upon Coronavirus Replication. Viruses, 73(11).
Leu, G., Lin, T., & Hsy, J.T. (2004) Anti-HCV activities of selective polyunsaturated fatty acids. Biochemical and Biophysical Research Communications, 318, 275-280.

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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References

Ahlstrand, T., Tuominen, H., Beklen, A., Torittu, A., Oscarsson, J., Sormunen, R., Pöllänen, M. T., Permi, P., & Ihalin, R. (2017). A novel intrinsically disordered outer membrane lipoprotein of Aggregatibacter actinomycetemcomitans binds various cytokines and plays a role in biofilm response to interleukin-1β and interleukin-8. Virulence, 8(2), 115–134. https://doi.org/10.1080/21505594.2016.1216294

Alnaseri, H., Arsic, B., Schneider, J. E., Kaiser, J. C., Scinocca, Z. C., Heinrichs, D. E., & McGavin, M. J. (2015). Inducible Expression of a Resistance-Nodulation-Division-Type Efflux Pump in Staphylococcus aureus Provides Resistance to Linoleic and Arachidonic Acids. Journal of bacteriology, 197(11), 1893–1905. https://doi.org/10.1128/JB.02607-14

Alnaseri, H., Kuiack, R. C., Ferguson, K. A., Schneider, J. E. T., Heinrichs, D. E., & McGavin, M. J. (2019). DNA Binding and Sensor Specificity of FarR, a Novel TetR Family Regulator Required for Induction of the Fatty Acid Efflux Pump FarE in Staphylococcus aureus. Journal of Bacteriology, 201(3), e00602-00618. https://doi.org/10.1128/jb.00602-18

Amiri-Jami, M., Abdelhamid, A. G., Hazaa, M., Kakuda, Y., & Griffths, M. W. (2015). Recombinant production of omega-3 fatty acids by probiotic Escherichia coli Nissle 1917. FEMS microbiology letters, 362(20), fnv166. https://doi.org/10.1093/femsle/fnv166

Aurand and March, “Development of a Synthetic Receptor Protein for Sensing Inflammatory Mediators Interferon-g and Tumor Necrosis Factor-a,” Biotechnology and Bioengineering, 2015.

Beermann, C., Möbius, M., Winterling, N., Schmitt, J. J., & Boehm, G. (2005). sn-position determination of phospholipid-linked fatty acids derived from erythrocytes by liquid chromatography electrospray ionization ion-trap mass spectrometry. Lipids, 40(2), 211–218. https://doi.org/10.1007/s11745-005-1377-1

Chanda, W., Joseph, T. P., Guo, X. F., Wang, W. D., Liu, M., Vuai, M. S., Padhiar, A. A., & Zhong, M. T. (2018). Effectiveness of omega-3 polyunsaturated fatty acids against microbial pathogens. Journal of Zhejiang University. Science. B, 19(4), 253–262. https://doi.org/10.1631/jzus.B1700063

Cho, Do‐Yeon, Skinner, Daniel, Lim, Dong Jin, Mclemore, John G, Koch, Connor G, Zhang, Shaoyan, . . . Woodworth, Bradford A. (2020). The impact of Lactococcus lactis (probiotic nasal rinse) co‐culture on growth of patient‐derived strains of Pseudomonas aeruginosa. International Forum of Allergy & Rhinology, 10(4), 444-449. https://doi.org/10.1002/alr.22521

Custodio, R., Johnson, E., Liu, G., Tang, C. M., & Exley, R. M. (2020). Commensal Neisseria cinerea impairs Neisseria meningitidis microcolony development and reduces pathogen colonisation of epithelial cells. PLoS pathogens, 16(3), e1008372. https://doi.org/10.1371/journal.ppat.1008372

Das U. N. (2020). Can Bioactive Lipids Inactivate Coronavirus (COVID-19)?. Archives of medical research, 51(3), 282–286. https://doi.org/10.1016/j.arcmed.2020.03.004

Das U. N. (2020). Response to: Bioactive Lipids and Coronavirus (COVID-19)-further Discussion. Archives of medical research, 51(5), 445–449. https://doi.org/10.1016/j.arcmed.2020.04.004

Deasy, A. M., Guccione, E., Dale, A. P., Andrews, N., Evans, C. M., Bennett, J. S., ... & Read, R. C. (2015). Nasal inoculation of the commensal Neisseria lactamica inhibits carriage of Neisseria meningitidis by young adults: a controlled human infection study. Clinical infectious diseases, 60(10), 1512-1520.

De Boeck, Ilke, Van den Broek, Marianne F.L, Allonsius, Camille N, Spacova, Irina, Wittouck, Stijn, Martens, Katleen, . . . Lebeer, Sarah. (2020). Lactobacilli Have a Niche in the Human Nose. Cell Reports (Cambridge), 31(8), 107674.https://doi.org/10.1016/j.celrep.2020.107674

Denis M. (1992). Interleukin-6 is used as a growth factor by virulent Mycobacterium avium: presence of specific receptors. Cellular immunology, 141(1), 182–188. https://doi.org/10.1016/0008-8749(92)90137-e

Denis, M., & Gregg, E. O. (1990). Recombinant tumour necrosis factor-alpha decreases whereas recombinant interleukin-6 increases growth of a virulent strain of Mycobacterium avium in human macrophages. Immunology, 71(1), 139–141.

Desvaux, M., Candela, T., & Serror, P. (2018). Surfaceome and Proteosurfaceome in Parietal Monoderm Bacteria: Focus on Protein Cell-Surface Display [Review]. Frontiers in Microbiology, 9(100). https://doi.org/10.3389/fmicb.2018.00100

Gullett, J. M., Cuypers, M. G., Frank, M. W., White, S. W., & Rock, C. O. (2019). A fatty acid-binding protein of Streptococcus pneumoniae facilitates the acquisition of host polyunsaturated fatty acids. The Journal of biological chemistry, 294(44), 16416–16428. https://doi.org/10.1074/jbc.RA119.010659

Gutierrez Jauregui Rodrigo, Fleige Henrike, Bubke Anja, Rohde Manfred, Weiss Siegfried, Förster Reinhold (2019). IL-1β Promotes Staphylococcus aureus Biofilms on Implants in vivo. Frontiers in Immunology, 10, 1082. doi: 10.3389/fimmu.2019.01082

Halleran, A. D., Swaminathan, A., & Murray, R. M. (2018). Single Day Construction of Multigene Circuits with 3G Assembly. ACS synthetic biology, 7(5), 1477–1480. https://doi.org/10.1021/acssynbio.8b00060

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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

Team:William and Mary/Engineering

Engineering Success

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Research

Table of Contents

1. Overview

Summary of Antiviral Effects of PUFAs

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 and Export by Microorganisms

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

8. Commensal Bacteria within the Nasopharyngeal Microbiome

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Imagine and Design

Table of Contents

Circuit Design

Case 1: Cytokine Concentrations Insufficient to Trigger High Pass Filter

Case 2: Cytokine Concentrations Surpass Threshold of High Pass Filter

Choice of Chassis and Safety Features

Genome Incorporation of Parts Protocol

Materials

Procedure

References

.

Build and Test

Table of Contents

1. Overview

2. Obtaining Parts

3. Constructing Circuits

4. Replicating PUFA Production Research

5. Testing Export Systems

5.1 - Directing Fatty Acids for Phospholipid Synthesis: AA

5.2 - Directing Fatty Acids to Phospholipid Synthesis: DHA

5.3 - Periplasmic Localization of Phospholipases

Periplasmic Protein Quantification: Gram Negative Bacteria

Motivation

Objectives

Reagents and Equipment

Reference

5.4 - Testing Overall Export Circuit

6. Testing Alternative Export Systems

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

Diverting Fatty Acid to Phospholipid Synthesis in Gram Positive Bacteria

Localization to the Gram Positive Periplasm

Periplasmic Protein Quantification: Gram Positive Bacteria

Motivation

Objectives

Reagents and Equipment

References

Testing Overall Export

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

Testing the Capability of FarE to Efflux AA

PUFA Differentiation (and Quantification) Protocol

Motivation

Protocol Objectives

Required reagents and equipment:

References

Reducing Competition between FarE and Phospholipid Synthesis

Testing Overall Export

7. Testing Cytokine Sensor

Testing of Cytokine Sensor Protocol

Motivation

Protocol Objectives

Required Reagents and Equipment

References

Quantifying Viral Titer

Motivation

Protocol Objectives

Required Reagents and Equipment

References

8. Testing Overall Circuit

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Learn and Improve → Research

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References