BACKGROUND

For the development of Rumino, the team needed a way to validate the biosensor using a viral sample. Ideally, we would test our device using avian influenza samples directly. However, due to the risks of using a pathogenic virus, this would not be feasible.

To have a way to safely validate nucleotide-based viral biosensors without the need of using the real target viruses, we developed RumiVec. This new composite part can produce single-stranded RNA phages with a test sequence embedded into its genome. As far as we are aware, there is no other system in the iGEM registry that is able to produce phages like this for use as a model organism. With a whole village dedicated to diagnostics and another one for infectious diseases, many team projects revolve around developing biosensors for quick viral detection. With our contribution we hope that teams are able to test and validate their viral sensors without relying on high-risk organisms. We decided to make a system for production of the MS2 phage specifically due to its small genome size, simplicity, and higher yield in synthetic-production methods compared to other single-stranded RNA bacteriophages [1].

AVIAN INFLUENZA

Bird Flu is a highly-contagious respiratory disease caused by infection of the Avian Influenza virus, mostly prevalent in poultry. This pathogen is part of the Influenza A genus, and is composed of an outer lipid-protein envelope and an internal protein coat which encapsulates its genetic content. The viral genome is composed of eight negative-sense single-stranded RNA segments, encoding a total of 11 proteins [1]. From these proteins, hemagglutinin and neuraminidase are often used as the basis for the classification of different strains of the virus (e.g. H5N1, H7N9, etc...) [1].

During the infection cycle, after the virus has hijacked the host's cells and started producing viral proteins, the hemagglutinin precursor must be cleaved by the host's proteases in order for the progeny to kill and leave the cell [2]. Most of the time, the cleavage site of hemagglutinin is recognized only by a limited set of proteases, which restricts infections to the respiratory and intestinal tracts of birds, resulting only in mild disease; strains like these are referred to as Low Pathogenic Avian Influenza (LPAI) [2]. However, certain types of the virus contain a stretch of basic amino acids in the hemagglutinin cleavage site. This small change significantly widens the set of proteases that can cleave the precursor, allowing for systemic infection and a near 100% mortality in birds; such strains are referred to as Highly Pathogenic Avian Influenza (HPAI) [2]. It's specifically HPAI the source of concern of the recent outbreaks of Bird Flu all across the world.

Figure 1. Structure of the Influenza Virus [3]

IMPACT

Avian Influenza is not just a zoonotic disease, but a global threat. Since 2020, Avian influenza has rapidly expanded across the world [4]. Due to its ability to rapidly mutate, the virus has been reported to have spread to 83 mammalian species, including cattle and wild birds [4]. Avian influenza cases have been reported in 108 countries, and on over five continents. With the increasing global rise of avian influenza, the United Nations has begun to take action accordingly. As of September 9, 2025, the Food and Agriculture Organization of the United Nations has organized the first global multisectoral dialogue, bringing together over 500 industry professionals and experts to discuss defense against Avian Influenza [4].

From an economic standpoint, avian influenza has devastated the agricultural and food industry on an international scale. In an attempt to control outbreaks, many farms resort to culling their entire flocks, which often includes healthy birds. The Canadian Government has officially reported that 533 farms have been impacted by avian influenza across all provinces, and 14,399,800 poultry have been culled in Canada [5]. In the United States of America, the Centers for Disease Control and Prevention has stated that 174,804,048 birds have been affected by HPAI since 2022. These numbers include commercial poultry, wild aquatic birds, and hobbyist flocks [6]. In terms of international numbers, the United Nations (UN) has reported that avian influenza has been the cause of death of over 300 million birds worldwide [7]. Farmers are seeing loss rates of 50% of their flocks [8]. As a result, farmers lose out on profits and are forced to cover costs related to the cullings [8]. In addition, the presence of HPAI has resulted in restrictions on the international trade of birds, impacting national economies.

Concerns about the spread of avian influenza in Alberta began in 2022. As of 2025, approximately 2,019,000 poultry have been impacted, making Alberta the province with the second most losses in Canada, just behind British Columbia [6]. With poultry and agriculture playing crucial roles in Alberta's economy, livelihoods and farms have suffered the most from the outbreaks.

The virus is not only impacting animals, but has also spread to humans. As of 2024, there have been 904 documented human cases of avian influenza, 464 of which were fatal [5]. The first case of avian influenza in Canada was a 13-year-old girl from British Columbia. She was hospitalized in critical condition due to acute respiratory distress. While human-to-human infection has yet to be observed, experts believe that avian influenza's genetic flexibility could increase the virus's infectiousness among humans [9]. The World Health Organization has recognized avian influenza to be a part of a family of viruses that are capable of causing pandemics [3]. Additionally, avian influenza remains foreign to the human immune system, and current vaccines are not designed to protect against avian influenza variants. With avian influenza rising as a global threat, it is crucial to act early through detection systems.

CURRENT LANDSCAPE

Currently, the avian influenza diagnostics' landscape is a trade-off between speed, sensitivity, and deployability [10, 11, 12, 13, 14]. Field-deployable antigen kits such as from Advacare Pharma and Ringbio dominate the frontline of outbreak response by producing quick, lateral-flow tests within minutes of poultry swabs [10, 11]. While field-deployable, their sensitivity is less than molecular methods. On the opposite end, lab-based PCR services (like IDEXX RealPCR and provincial diagnostic labs) offer gold-standard accuracy but require centralized facilities, shipment delays, and greater cost which is less than perfect for real-time field-level applications [12, 13, 14]. A third category, antibody-based ELISA kits like the IDEXX AI Ab Test, measures exposure history, not active infection, offering value for long-term surveillance but little application during outbreaks [13].

Alberta farm operator and veterinarian inputs highlight the fact that no single tool adequately addresses all of these areas of need: true field deployability, timely outbreak detection, cost-effectiveness, and adaptability are unmet needs. This diagnostic framework is the market that Rumino is participating in where Rumino is combining the portability of antigen kits with the sensitivity of molecular testing to bridge the gaps in existing solutions. For a more comparative and market analysis, visit the Entrepreneurship page.

RUMINO

The Biosensor

Rumino is in essence a nucleic acid biosensor capable of detecting specific sequences. This can be used for viral detection by targeting sequences that are unique to the genomes of specific species or strains of viruses. With this project, we aim to provide the fundamental bases for the development of a modular technology for point-of-care detection of pathogens. Rumino provides a platform to quickly tackle current and emerging health threats by providing a way to easily change between targets.

Rumino took heavy inspiration from the ultra-sensitive single-tube biosensor (USTB) developed by Sun, et al [15]. This system immobilized single-stranded oligos, modified with a hydrophobic chain, on the surface of a glass tube which would cause water to fall from the bottom of the tube if it was inverted [15]. Once the target sequence is detected, the immobilized oligos are released which turns the surface hydrophilic, allowing water to stay stuck to the bottom when the tube is inverted [15]. USTB makes use of a Cas endonuclease, which will be activated in the presence of a target sequence, and as a consequence it will cleave the oligos from the surface, leading to their release [15]. In a laboratory-setting, this sensor can detect specific DNA/RNA sequences at concentrations 1 aM, and without the use of any sophisticated equipment [15]. Due to the extremely high sensitivity and the fact that no equipment is needed for this assay, we decided to base our biosensor using this same wettability-change mechanism.

Rumino employs a glass capillary tube as the main body/frame of the sensor. Capillary tubes are characterized by the ability to either pull or push liquids above/below the liquid's surface level. The height of the rise is given by Jurin's Law, which dictates that this value depends on the surface tension of the liquid (γ), the contact angle between the liquid and the tube's surface (θ), the density of the liquid (ρ), gravity (g), and the radius of the tube (r) [16].

Figure 2. Capillary rise and contact angles in a capillary tube.

The surface tension and density are inherent to the type of liquid [17], the gravity is obviously a constant for our purposes, and the radius will remain consistent for the same tube. The contact angle, however, depends on the type of surface that makes up the tube’s walls, and the interactions between the liquid and this surface (i.e. surface wettability) [17]. For a polar liquid (e.g. water), if the surface is hydrophilic, then the contact angle will be smaller than 90°, which means the liquid will be pulled above the surface [17]. If the surface is hydrophobic, the contact angle will be greater than 90°, meaning the liquid will be depressed under the surface [17].

What all of this means is that by modifying the physical properties of a surface, a visible change can be produced in the liquid rise within capillaries. The USTB system managed to change the wettability of glass using modified oligonucleotides immobilized to the surface of a glass tube [15]. Based on this precedent, Rumino assembles a similar mechanism inside a capillary tube, which offers some unique benefits. In terms of production, a capillary tube has a smaller surface area requiring less reagents to assemble, is easier to scale up in manufacturing, and due to its smaller size it’s also easier to transport.

Rumino covalently immobilizes a substrate strand to the inner surface of a capillary tube which is then hybridized to an incumbent strand. The incumbent is modified with a long carbon chain at one end (Laurylamine), making the surface hydrophobic when the incumbent is hybridized to the substrate. Once the target is added, it will displace the incumbent and remove it from the surface, causing the surface to become hydrophilic. For the user, this means that when a sequence specific to HPAI is introduced to the tube, the water will climb up, serving as a simple and easily recognizable signal for a positive result. We've performed several experiments to build a proof-of-concept that demonstrates the potential of this technology as a novel biosensor.

The Sequence

A key component of the biosensor is a sequence that can uniquely target Highly Pathogenic Avian Influenza (HPAI), without triggering a signal for Low Pathogenic Avian Influenza (LPAI). The best way to find the target sequence is to look in the cleavage site of the hemagglutinin gene of fragment 4, as this is where the defining differences between LPAI and HPAI are [same source as in background info]. Using ClustalOmega [19], a multiple-sequence alignment was done with three chicken strains and three cattle strains of HPAI, which showed a high degree of conservation in the cleavage site (1015-1035).

Figure 3. Multiple Sequence Alignment of three chicken and three cattle HPAI strains sourced from the US. The underlined sequence represents the polybasic cleavage site characteristic of HPAI strains.

Given that the conservation between HPAI strains is high but not perfect, the target sequence was slightly extended past the cleavage site to make the system more tolerable for mismatches and at the same time more specific towards Avian Influenza and not any other sequence that might be present in the sample.

CCTCTAGAGAAAGGAGAAGAAAAAGAGGCCTGTTTGGGGCGATAGCAGGG

To verify the specificity of the sequence, a basic local alignment of the target sequence was performed using BLAST (with a modified expected threshold = 0.1). The target was compared against chicken (Gallus gallus), and the most common microbiota of the poultry oropharynx: Streptococcus suis, Chlamydia ibidis, Gallibacterium anatis, Avibacterium paragallinarum, Mycoplasma gallinaceum, and Weissella confusa [20]. No other sequence with significant alignment was found which indicates a very low possibility of the sensor being set off by a sequence endogenous to the sample environment.

Although we tested the target against the sequences of other organisms in the sample, it is still crucial to verify that our sequence is specific to HPAI and won't produce a response to LPAI infections. For this purpose, a program was made that takes the nucleic acid and protein sequences of the Hemagglutinin gene of an Avian Influenza sample and classifies it as either LPAI or HPAI based on the presence or absence of a basic motif in the cleavage site. This program was combined with an alignment algorithm which takes in different H5N1 Influenza sequences of Fragment 4 along with a chosen target sequence, and tells the user the amount of LPAI and HPAI strains the target aligns or does not align to.

Figure 4. Workflow for verifying specificity of target sequence.

All 13,868 of the North American H5N1 Fragment 4 sequences uploaded in NCBI Virus [source] were downloaded and tested with the RumAlign program. The chosen target sequence has a predicted false positive rate of 0.097% and a false positive rate of 0.0% when compared with fragment 4 sequences of the H5N1 Influenza virus.

The Final Product

Although crucial, the biosensor itself is only a small piece of the final product. Given that Rumino is intended to be used in the field for detection of HPAI, many different considerations and components are necessary for the design of the test kit. For this initial version, Rumino will be used to test oropharyngeal swabs from poultry suspected of being infected with HPAI. Oropharyngeal swabs are the preferred method to obtain a sample from chicken for testing as this is the site with highest amounts of viral shedding [21].

With this in mind, we designed a test kit containing several components:

Container	Component	Purpose
EtOH plastic container	75% Ethanol	Disinfecting samples for user safety [22] and buffer solvent
Sample container (Lyophilized)	N-Acetyl Cysteine	Sample liquefaction [23]
	Sodium Dodecyl Sulfate	Viral lysis, RNAse inhibition, and RNA denaturation
	Proteinase K	Degrade RNases and assist in viral lysis
	Calcium Acetate	Proteinase K stabilization [24]
	Phosphate Buffer Saline salts	pH buffer
Silica gel pouch	—	Absorbing moisture
Kit box	Cotton swab	Collecting sample
	Plastic pipette	Transferring liquids between containers
Biosensor zipper bag	Test capillary	Biosensor for detection
	Control capillary	Negative control
	Silica gel pouch	Absorbing moisture

Figure 5. Components of the Rumino test kit for sample preparation and testing. Certain items such as a biohazard disposal bag and the safety sheet are not illustrated here. For a full description of the test-kit components, please visit our entrepreneurship page.

The kit was designed to mitigate false results as this is one of the biggest concerns that have been addressed to us by several stakeholders and experts in the field (See IHP). For example, a false positive result could potentially halt all operations in a poultry farm, harming farmers and wasting the time and resources of veterinarians. On the other hand, a false negative would result in a poultry farm to continue operations as usual even if the animals are infected with HPAI, posing a huge risk to public health and potentially leading to the farm becoming ground-zero for an outbreak.

There are two main reasons that a false positive result would arise. If there's a non-HPAI sequence similar to the target, this might falsely trigger the detection signal; however this was heavily mitigated by the software analysis which showed that the target sequence isn't significantly similar to any other sequences that might be present in the sample, or to any LPAI sequences. Degradation of the sensor components would also lead to a false positive result. This is mitigated in the kit by lyophilization of the components, which significantly increases shelf-life and stability, along with the silica gel pouches which protects the sensor from humidity. Extreme pH changes would also result in degradation of key components, but the PBS salts in the sample buffer should keep the system at a stable pH. More importantly, a negative control capillary tube is included within the kit. This capillary is functionalized only with a single-stranded oligonucleotide modified with a hydrophobic group, which means that no change in water rise should be observed in this specific capillary even when the target is present (in this specific capillary).

On the other hand, the main reason for a false negative result would likely be too little target present in the testing solution. As a way to maximize the amount of target sequence used for the assay, both SDS and Proteinase K are included in the sample buffer which should effectively lyse viral particles and release their genetic content, but most importantly they can both degrade and inhibit enzymatic degradation of RNA.

With all these precautions described, Rumino mitigates both false positives and false negatives to deliver a responsible and safe product to be used by farmers and vets alike.

WHAT'S NEXT?

Our team has built the foundation for a novel biosensor technology for accurate detection of infectious diseases. To develop Rumino past the laboratory and into the field, we have outlined the next steps that need to be taken in the section below. Here we will specifically describe the next steps for the technical development of the technology. For details on Rumino's future direction as a start-up business, visit our Entrepreneurship page on the website.

The first and most important priority will be improving the sensitivity of the system. According to our experiments, the TMSD mechanism inside the capillary has a limit of detection (LOD) of at most 100 nM. For a diagnostic device, Rumino needs to achieve a LOD in the picomolar-attomolar range. To increase the sensitivity of the system, several approaches can be taken to modify the system. One of the easiest and fastest ways to get a boost in sensitivity is by fully optimizing the reactions for functionalizing the surface of the capillaries. For our experiments we followed a quick and easy reaction scheme set out by Sun, et al [15], but by tailoring the reactions to better fit our purposes, we could end up with a higher degree of functionalization which would likely lead to improved sensitivity. The potential to obtain exceptionally high sensitivity is supported by other studies that show a LOD in the femtomolar range with TMSD systems without the need of enzymes or proteins [24]. Our dry lab has also developed a model that could speed up the TMSD reactions as well as software that can streamline the design process for the sequences required. These models can be viewed in our Dry-Lab pages.

Secondly, Rumino has only been tested using DNA targets; however, the HPAI virus has an RNA genome. For this reason, the system must first be tested with pure RNA strands containing the target sequence to make sure the sensor is ready for the next steps. Current literature shows that none or only minor modifications would be needed, as the efficiency of TMSDs using DNA substrates with RNA targets is similar to that of a system using only DNA [25].

Once these two points have been addressed, the entire kit must be tested using viruses and with samples that mimic oropharyngeal swabs. For purposes of safe validation, our team has developed RumiVec, a phagemid system that can produce single-stranded RNA phages containing any control sequence desired. We would engineer RumiVec to contain the target sequence and then use its products as a way to model the Influenza virus. Using bacteriophages as models will allow us to address and resolve future optimization issues, going through different iterations without spending significant resources and time obtaining and testing clinical samples.

Apart from point-of-care diagnostics, our team is aiming to develop a continuous monitoring system for environmental testing. This technology would be used as an early detection system near farms to monitor outbreaks and warn farmers of infected wild birds near the area. A lot more work is still needed before we can reach a minimum viable product, including thorough research into the conditions the sensor would be subjected to, along with the range of sample compositions. However, to make some progress on this aspect, we have started working on a rudimentary prototype of the hardware needed for such an endeavor. Our work for this is explained in detail in our Hardware page.

Rumino is more than just a diagnostics sensor for HPAI. We strive to offer a universal modular platform to combat the spread of any infectious disease by monitoring outbreaks, and providing a system that can quickly pivot to target emerging health threats.

REFERENCES

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