Overview of Project DR. SWITCH (Disease-associated RNA Switch)

Our project focus on developing an on-site subtyping method for Influenza A virus subtype H5N1 and H7N9 using toehold switches. To facilitate future toehold switch project, we also developed an online software program for designing toehold switch, and constructed toehold switch cloning tool that allow easy construction and validation of toehold switches.

Influenza A is a rapid changing disease that causes 5,000,000 of death annually worldwide. Among different subtypes, highly pathogenic avian influenza has the highest mortality rate. Challenges of disease control in the modern world with high population mobility remains at the speed and accuracy of diagnosis. However, nowadays influenza A subtyping method relies greatly on RT-PCR, which requires long time, expertise and laboratory space. Meanwhile, a novel type of riboswitch, namely toehold switch, shows its potential in subtyping Influenza A with quicker detection and lower production cost.

By combining cell free system and toehold switch, a rapid on- site detection method for influenza A subtype H5N1 and H7N9 is designed and under investigation. It has high potential to be used widely in, but not limited to, animal farms, and border inspections and schools wherever expertise and laboratory equipment are not readily available.

We hope that our project can

1. Provide rapid detection method with higher accuracy at a lower production cost;
2. Stop Influenza A pandemic by early on-site detection; and
3. Ease the stress on public health service when disease attacks, especially in less developed countries.

Influenza Type A

Influenza is a prevalent acute respiratory disease circulating among human and other animals (1). Influenza A can be spread rapidly throughout poultry flocks and cause severe illness, or even death in human. The most notorious pandemic was the “Spanish Flu” in 1918, which killed 50 million people worldwide (1). Influenza A virus poses large social and economic burden. Each year in the United States, it is estimated that around 600,000 lives and $90 billion US dollars are lost due to influenza A virus (2). The existing form of influenza virus genome is segmented antisense RNA. Influenza A can be subtyped according to the types of hemagglutinin (HA) and neuraminidase (NA) glycoprotein on the virus surface (above figure). NA protein can cleave terminal sialic acid residue and promote virion release (3). Since there are 18 types of HA and 11 types of NA, there are 198 possible subtypes. Different influenza A subtypes possess different properties. For example, the mortality rate of infection by the subtypes H5N1 and H7N9 is much higher than that of H1N1.

Avian influenza

In this project, we aim to construct a set of artificial RNA biosensors to detect different influenza A viral genes, including the hemagglutinin and neuraminidase genes. We consulted local medical expert (link) and found that there is an urgent need for fast and on-site subtyping method for Avian influenza compared with other subtypes in Hong Kong.

Avian influenza are influenza A viruses that adapted to birds, which can be classified into high pathogenicity (HP) or low pathogenicity (LP). Highly pathogenic avian influenza (HPAI) are originally intransmittable among human, but later inherited pathogenic property from other influenza A viruses through reassortment (3). For example, both pathogenic properties of H5N1 and H7N9 are suspected to be inherited from H9N2 (3). Since Hong Kong is a stopover point of migrating birds (4), the chance of avian flu outbreak in Hong Kong is much higher than in other places. Together with the fact that Hong Kong is a highly populated city with great passenger throughput per day, any outbreak of avian flu in Hong Kong may easily cause pandemic.

Therefore, we focused on constructing biosensors for subtyping the notorious Avian influenza. Among the subtypes, subtypes H5N1 and H7N9 are the most urgent subtypes that require need method to diagnose.

H5N1: The notorious flu

H5N1 is the most notorious highly pathogenic avian influenza. The first epidemic outbreak of H5N1 in human happened in Hong Kong in 1997. The flu was then spread to the entire Asia. According to the World Health Organization, there was 859 confirmed human cases since 2003 which killed 453 people with a mortality rate of 52% (5). The disease not only create tremendous economic burden to the health care system, it also greatly impact the poultry industry. During the outbreak of H5N1 in Hong Kong, 3.5 million chicken was slaughtered. About $10 billion US dollars had lost due to H5N1 outbreak (6). Although the risk of H5N1 pandemic outbreak in human population is considered to be low recently, it is considered as endemic in poultry in six countries (Bangladesh, China, Egypt, India, Indonesia, and Vietnam) (7).

H7N9: The next H5N1?

H7 virus was thought to be only circulated among avian hosts but human infection is recently reported. The first case of human infection was recorded in China in 2013 (8). According to the World Health Organization (WHO), 1533 human infection cases were reported, with a mortality rate of 39% (9). In Hong Kong, 4 confirmed human cases were reported so far. H7N9 cased economic loss of about $6.5 billion in China (10). Among all the avian influenza virus, H7N9 virus was found to have the highest ability to infect humans and circulate in birds (11). WHO warned that the human infections are unusual and need to be carefully monitored. According to the Centers for Disease Control and Prevention (CDC) of the United States (12), H7N9 is the subtype that has the greatest potential to cause a pandemic in recent year compared with other subtypes. It is worried that H7N9 may cause next pandemic since the virus is evolving mechanism for human- to- human transmission (13).

The need for new subtyping method

To avoid possible epidemic and pandemic outbreak, World Health Organization (WHO) has a well-established Global Influenza Surveillance and Response System (GISRS) (3). With combined effort of more than 120 national laboratories, the potential epidemic strain of influenza A virus will be selected to make vaccine to prevent possible outbreak (3). To effectively monitor the spread of avian influenza, a simple and rapid on- site method is needed for detecting the virus in both human and poultry. However, nowadays on-site diagnostic method, such as Rapid Influenza Diagnostic Tests (RIDTs), can only identify the influenza A virus but cannot subtype it (14). Traditional influenza A subtyping method rely on qRT-PCR (15). Although the technique is highly sensitive and specific (16) , it is not suitable to be relied on during the spread of disease, since it requires long time, and cannot perform in poor condition where expensive equipment and technical expertise are not available. Failure of immediate respond to the spread of disease may result in pandemic (17). Meanwhile, a novel type of riboswitch, namely toehold switch, shows its potential in detecting viral RNA on- site with short detection time and low production cost.

RNA toehold switches

The artificial RNA biosensors we used is called toehold switch, which is first developed and published in 2014 by Green et al (18). It is a motif in mRNA that allows the translation of downstream protein coding sequence when a specific trigger RNA binds to it. The trigger RNA binds to the switch region of the toehold linearizes toehold secondary structure. This then releases the Ribosomal Bing Site (RBS) from the loop, allowing a ribosome to bind on it. The ribosome can then read along the coding region of the toehold switch, hence giving off a signal.

Cell free system

Cell free system is a mixture of cytoplasmic and nuclear components from E. coli for in vitro transcription and translation (Sitaraman, 2004). Recent studies revealed that cell free system can be stored in room temperature after freeze drying (Pardee et al., 2014). Activation of the freeze dried synthetic genetic network can be done by adding water. It has also been demonstrated that complicated genetic network can function on the paper with cell free system (Pardee et al., 2014). Our toehold switch technology will further apply in cell free system to allow on-site detection for influenza A in. It has a high potential to be used widely in, but not limited to animal farms and border inspections wherever expertise and laboratory equipment are not readily available. Recent findings showed that toehold switches can be used to detect Zika virus and Ebola virus (19, 20). However, to the best of our knowledge, none of the up- to- date research has shown that toehold switch can be used to subtype Influenza A while existing technology shows limited advantages on Influenza A diagnosis.

Altogether, the project aims to apply toehold switch technology in influenza A subtyping and offer convenient tool to facilitate the design of toehold switch. It is hoped that our method could suppress the spread of pathogenic Influenza in a timely manner.

Reference:

1. Global Influenza Programme [Internet]. World Health Organization. 2017 [cited 31 May 2017]. Available from: http://www.who.int/influenza/en/
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4. Huaiyu Tian, Sen Zhou, Lu Dong, Thomas P. Van Boeckel et. al. Avian influenza H5N1 viral and bird migration networks in Asia. Proc Natl Acad Sci U S A. 2015 Jan 6; 12(1): 172–177.
5. "Cumulative Number of Confirmed Human Cases for Avian Influenza A/(H5N1) Reported to WHO, 2003-2017" (PDF). Who.int.
6. Rosenthal, E; Bradsher, K (2006-03-16). "Is Business Ready for a Flu Pandemic?". The New York Times. Retrieved 2017-08-23.
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9. Monthly Risk Assessment Summary. (2017). World Health Organization. Retrieved 5 July 2017, from http://www.who.int/influenza/human_animal_interface/HAI_Risk_Assessment/en/
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12. "Avian Influenza A (H7N9) Virus | Avian Influenza (Flu)". www.cdc.gov. Retrieved 24 February 2017.
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14. Landry ML. Diagnostic tests for influenza infection. Curr Opin Pediatr. 2011 Feb;23(1):91-7.
15. Daum LT, Canas LC, Arulanandam BP, Niemeyer D, Valdes JJ et. al. Real-time RT-PCR assays for type and subtype detection of influenza A and B viruses. Influenza Other Respir Viruses. 2007 Jul;1(4):167-75.
16. Tsushima Y, Uno N, Sasaki D, Morinaga Y, Hasegawa H, Yanagihara K. Quantitative RT-PCR evaluation of a rapid influenza antigen test for efficient diagnosis of influenza virus infection. J Virol Methods. 2015 Feb;212:76-9.
17. Ross AG, Crowe SM, Tyndall MW. Planning for the Next Global Pandemic. Int J Infect Dis. 2015 Sep;38:89-94.
18. Green AA, Silver PA, Collins JJ, Yin P. Toehold switches: de-novo-designed regulators of gene expression. Cell. 2014 Nov 6;159(4):925-39.
19. Pardee K, Green AA, Ferrante T, Cameron DE, DaleyKeyser A, Yin P, Collins JJ. Paper-based synthetic gene networks. Cell. 2014 Nov 6;159(4):940-54.
20. Pardee K et. al. Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components. Cell. 2016 May 19;165(5):1255-66.