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A Risk Assessment of the Potential Use
of Gene Drives in Infectious Diseases
Shambhavi Naik
1
Executive Summary
Gene drives are being explored
for alleviating vector-borne
infectious diseases however, the
risks of employing them need to
be understood.
This document assesses the
potential use of gene drives in
India by performing a stage-wise
risk assessment of deploying gene
drive.
2
Gene drive mosquitoes are an application of Clustered Regularly
Interspaced Short Palindromic Repeats (CRISPR) technology. The
application is to develop mosquitoes that decrease the incidence
of mosquito-borne diseases.
Current research into engineering these mosquitoes is being
funded by the Bill and Melinda Gates Foundation, Defense
Advanced Research Projects Agency (DARPA) and more recently,
the Tata Trusts. A British company, Oxitec has also been
experimenting with CRISPR in Cayman Islands, Brazil and
Maharashtra.
Research into gene drives should be promoted however, there are
risks associated with their potential use in India. Given the nature
of the technology, it is recommended that robust monitoring
mechanisms for disease incidence, mosquito burden and
ecological impact be implemented before deploying these
mosquitoes.
Data driven decisions on identifying the type of gene drive and
deployment locations will ensure effective use of the technology.
Gene drives and infectious diseases
• In India, infectious diseases have a high economic burden.1
• Gene drives refer to Gene Edited Mosquitoes (GMM) which can pass on their gene modification to
future generations of mosquitoes.
• Scientists are currently developing GMMs to help alleviate incidence of malaria and dengue, amongst
other vector-borne diseases.
• Given the economic burden of vector-borne infectious diseases in India, it is prudent to explore gene
drive technology for eradicating the diseases. However, the technology is still in its nascent stages and
an appropriate risk assessment is necessary to make an informed decision and initiate public dialogue
over its use.
3
Stage 1:
CREATE GMM
Stage 2:
DEPLOY
Stage 3:
MONITOR
1. Choose target area for field
trial
2. Evaluate disease
burden/mosquito population
prior to trial
3. Evaluate disease
burden/mosquito population
post trial
4. Calculate and deploy GMM
based on incidence data and
efficacy of GMM as evaluated
through trials
1. Continued surveillance of
GMMs and ecosystem to
ensure early detection of any
unintended consequences
1. Select the disease to target
through GMM
2. Identify the pathogen
strain(s) present locally
causing the disease
3. Identify the local vector
species
4. Choose the most effective
GMM strategy to target the
disease (see on Page 7)
Steps and stages involved in using a gene drive
4
Risk determination matrix
Parameters Low Risk Medium Risk High Risk
Ease of Mitigation Best practices available Best practices available
Best practices not yet
established
Number of stakeholders
involved
(Ease of implementing mitigation
measures)
Only one (laboratory level)
Multiple (Lab +
governmental agencies)
Multiple (Lab +
governmental agencies)
Probability of Occurrence Low Medium High
5
Glossary
Ecosystem – includes humans, animals and plants.
Humans.
Laboratory/Institution: The organisation (private or
government) that will create the GMMs.
Government: Governmental agencies (Local, State
and Union) responsible for monitoring disease
burden (National Vector Borne Disease Control
Programme) and approving gene drive research and
release.
Key participants and
their role in gene drive
development and usage
6
Stage 1: Create GMM
GMMs are engineered in laboratories of either private or public institutions. The designated laboratory would have
to demonstrate containment facilities that meet the required safety standards for the containment of mosquitoes
and the pathogen under study. Trained personnel will be required to perform experiments and laboratory trials.
There are two known strategies in designing the GMM:
Population Suppression - Decrease fertility of
mosquitoes2
This approach designs a modified male mosquito that
upon mating with a wild-type female will result in an
unviable offspring. Thus, over time, the mosquito
population will decrease and subsequently, the gene drive
will disappear. The disadvantage of this approach is that
modified male mosquitoes will need to be released into the
environment every season till the entire species is wiped
out.
Population Replacement - Reduce capability of GMM to
carry pathogen3
This approach introduces an anti-pathogen peptide in the
mosquito, so that it can no longer host the pathogen. So
the mosquito species survives and continues to pass the
modification to its offspring. The disadvantage of this
approach is that the genetic modification will remain in
the environment forever, increasing the likelihood of
unintended consequences.
7
CREATE DEPLOY MONITOR
LOW RISK PROBABILITY
Risk 1a: GMMs have non-target mutations
• Submission of genetic sequencing data for GMM should be obligatory for deployment approval. Data should highlight any changes in gene
sequences and resulting physiological changes in GMM.
• Government approval to field trials and environmental release of the GMM should be contingent on demonstration of no other functional
change than that described in the proposal.
Recommendations
In 2017, Schaefer et al4, reported the
presence of unexpected mutations in mice
edited using CRISPR. However, the paper
was retracted5 in March 2018 following
criticism that all mutations may not have
been caused directly by CRISPR. The
presence of non-target mutations is still
being debated and hence, as a precaution,
should be tested in GMMs.
Laboratory should conduct exhaustive
studies to identify non-target genetic
changes through gene sequencing across
GMM generations. Phenotypic changes in
GMM as a result of the mutations should be
documented. All non-target mutation data
studies should be done prior to deployment
of the GMM.
Risk Evidence Potential Mitigation
Gene editing can lead to non-target
mutations which may have physiological
effects. GMMs may become resistant to
insecticide, may harbor other pathogens or
may not be effective at preventing the
disease they were designed against. Both
population suppression and replacement
approaches have similar potentials of
carrying non-target mutations.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison
=
Glossary Ecosystem Humans Labs/Institutions Government
8
CREATE DEPLOY MONITOR
LOW RISK PROBABILITYRisk 1b: GMM or pathogen becomes resistant to the
genetic modification
• Include a molecular marker to identify GMM for sampling.
• Approval for deployment should be contingent on demonstration of resistance studies. A threshold for number of generations within which
resistance may appear should be preset to avoid those GMMs which would be vulnerable to development of resistance quickly.
• Ensure proper monitoring mechanisms are set to capture GMMs for sampling.
Recommendations
Scientific reports suggest that GMM
created to lose viability may develop
resistance to the modification.6,7 A similar
selection-based resistance has been
observed with the boll worm which
developed resistance to the toxin secreted
by BT cotton plants.8
Exhaustive studies must be conducted to
assess when resistance develops across
GMM generations. Equivalent resistance
studies in pathogens would be difficult
because of the requirement of human host
for completion of life cycle. Monitoring
mechanisms should be put in place to
sample the deployed GMM for development
of resistance.
Risk Evidence Potential Mitigation
GMM or pathogen may become resistant to
the genetic modification. As species evolve,
they may find a way to escape modifications
if it does not provide a significant survival
advantage. The population suppression
approach may be susceptible to resistance
development, since the approach is lethal to
mosquitoes and evolution pressures will
select for resistant mutations.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison
>
9
Glossary Ecosystem Humans Labs/Institutions Government
CREATE DEPLOY MONITOR
LOW RISK PROBABILITYRisk 1c: GMMs or pathogens escape from the
Laboratory/Transport
• Government approval for gene drive research should be contingent on demonstration of necessary infrastructure and Good Lab Practices
(GLP) compliance.
• Appropriate training for personnel working in laboratory or transport facilities and periodic assessment of the training should be obligatory.
• Funding for gene drive research should include resources for developing and maintaining the infrastructure and best practices.
Recommendations
Pathogens have been known to escape from
laboratories and infect individuals in the
past.9 The main cause has been poor
infrastructure and containment facilities.
Escape of mosquitoes is also possible and
the Food and Agriculture Organization of
the United Nations has issued guidelines for
colony maintenance of mosquitoes.10
Handling and containment of GMM and
pathogens should follow best practices
established worldwide. Access to GMM and
pathogen should be restricted to trained
personnel. Pathogen cultures should be
maintained in GLP-compliant facilities
under appropriate containment measures.
Risk Evidence Potential Mitigation
If experimental mosquitoes are released,
they may influence the environment by
mating with other mosquitoes. However,
given the low number of GMM that may
escape, their impact will be minimal. If the
pathogen escapes, it may infect lab
personnel and residents in the leak’s
vicinity. However, given that the spread of
the pathogen requires a vector, risk is low.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison =
10
Glossary Ecosystem Humans Labs/Institutions Government
Create GMM - Recommendations
• Government should set standards for institutions
wishing to conduct gene drive research. Such
standards should include the demonstration of
necessary infrastructure, GLP compliance and
training of personnel.
• Government should set standards for GMMs to be
deployed in the environment. These should include
the presence of a molecular marker for
identification, absence of functional non-target
mutations and minimum number of generations
tested for resistance development.
• Appropriate training for personnel working inside
laboratory or transport facilities and periodic
assessment of the training should be obligatory.
• Funding proposals should include resources for
developing and maintaining the infrastructure and
best practices.
• Laboratories wishing to do gene drive research
should follow GLP guidelines and best practices as
outlined by the government to ensure containment
of mosquitoes and pathogens.
For Laboratories: For Government:
11
Stage 2: Deploy
Once a GMM has been designed and tested under laboratory conditions,
field trials would be conducted in select locations. Deployment of GMMs
would be approved contingent upon satisfactory results from the field trials.
12
CREATE DEPLOY MONITOR
HIGH RISK PROBABILITYRisk 2a: GMMs get deployed at inappropriate spaces
because of inaccurate burden data
• The first step for GMM deployment would be to capture and validate accurate data on disease burden through improved reporting systems.
• Data on hotpots for mosquito breeding sites would be necessary to ensure appropriate deployment of mosquitoes.
• Analysis of these data to generate predictive models for forecasting breeding hotspots would be beneficial for identifying targets for GMM
deployment.
Recommendations
Studies have reported that dengue
incidences in India are nearly 300 times
higher than official reports.11 The incidence
of malaria has been inconsistent with WHO
estimating 15,000 casualties/year, while
other studies suggest a plausible casualty
range between 125000 – 277000 people
annually in India.12
Monitoring mechanisms should be set up to
determine disease and mosquito burden
before deploying GMMs. A comprehensive
study report of the area to be targeted
along with analysis of disease burden,
mosquito burden and demographic studies
should be performed before deploying
GMMs.
Risk Evidence Potential Mitigation
Infectious disease burden has been
underreported in official records and
current inefficient mechanisms of reporting
could lead to misidentification of disease
hotspots. Absence of robust real-
time/predictive data could lead to
deployment of GMMs in incorrect spots
thereby reducing their efficiency to combat
the disease.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison =
13
Glossary Ecosystem Humans Labs/Institutions Government
CREATE DEPLOY MONITOR
HIGH RISK PROBABILITYRisk 2b: Migration of mosquitoes affects efficacy of
GMMs
• Constant monitoring of mosquito populations to identify any changes.
• For any significant change in population of any particular species, measures should be put in place for population control.
• For state border areas, interstate bodies should agree on a single action plan for deploying GMMs.
Recommendations
Mosquitoes generally live in the vicinity of
their breeding sites – travelling roughly 50
– 100 meters. However, they can travel
further in search of food resources. Some
mosquito species have been known to
travel as far as 100-150 km.13
Stronger reporting systems would facilitate
data-based deployment of GMMs.
Migration may be combated by increasing
the deployment of GMMs. Interstate
cooperation would be required, particularly
in the border areas to ensure efficient use
of GMMs.
Risk Evidence Potential Mitigation
India has favourable weather for mosquito
breeding. Expanding city limits provide
additional breeding sites. Thus, it is likely
that deployment of GMMs may be
hampered by migration of mosquitoes from
adjoining areas. This is particularly true in
population suppression strategy where the
availability of food resources may act as an
added attractant.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison >
14
Glossary Ecosystem Humans Labs/Institutions Government
CREATE DEPLOY MONITOR
MEDIUM RISK PROBABILITYRisk 2c: Spread of mosquitoes/pathogens across the
country would affect the efficacy of GMMs
• Mosquito populations must be constantly monitored to identify changes.
• GMM deployment should be done concomitant with ongoing measures for mosquito control.
• Government should take expert opinion before approving field trials to prevent overlap of GMMs from different sources.
Recommendations
For example, there are six primary vectors
(Anopheles culicifacies, An. dirus, An.
fluviatilis, An. minimus, An. sundaicus and
An. stephensi) for malaria in India and five
of them operate in species complexes.14
Their distribution across India is variable
and needs to be studied locally to define the
GMM strategy.15
A targeted approach identifying the disease
and vector spectrum to be used for GMM
has to be identified.
Risk Evidence Potential Mitigation
India is home to a wide spread of disease-
causing mosquitoes and pathogens. Even
for a single pathogen there are various
existing vectors. Hence, even if one
mosquito species is targeted, the pathogen
may just proliferate in another vector
species. Thus, for GMM strategy to work, all
vector species for a target pathogen species
would need to be modified.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison =
15
Glossary Ecosystem Humans Labs/Institutions Government
For Deploying Agency: For Government:
Deploy - Recommendations
• Target areas for deployment/field trials should be
based on evidence of mosquito breeding hotspots.
Mosquito population/disease incidence should be
measured for at least 3 years before deployment and
3 years post deployment.
• Sampling of mosquito populations/disease
incidence should be performed according to
government prescribed standards.
• Any changes in mosquito populations or disease
incidence should be immediately reported to the
designated governmental authority and laboratory.
• Guidelines and best practices for measuring
mosquito populations/disease incidence should be
prescribed.
• Field trial/deployment approval should be given by a
committee of scientists, ecologists and citizens.
• Awareness about GMMs and public engagement over
their possible effects should be created before field
trials. Representatives from both the laboratory and
deploying agency should be present for such
engagement.
16
Stage 3: Monitor
Post deployment of mosquitoes, the ecosystem should be
continuously monitored for changes in disease incidence,
mosquito populations and food chain impacts.
17
CREATE DEPLOY MONITOR
Risk 3a: GMM have a negative impact on the food chain
• Mathematical modelling and field testing should be done to simulate the impact of population loss on the food chain.
• Identification of species dependent on mosquitoes in the area of deployment should be made and their populations should be monitored
for changes.
Recommendations
There is considerable debate on how
important mosquitoes are in the food chain.
Male mosquitoes are not primary
pollinators of crops required for human
consumption. Predators may also quickly
find other insects to fill up their diet.
However, specialised predators like the
mosquitofish may be severely impacted.16
Mathematical and field testing should be
done to simulate the impact of population
loss on the food chain. Gene drive
strategies which inhibit the pathogen
instead of reducing mosquito populations
may be preferred.
Risk Evidence Potential Mitigation
Mosquitoes are a part of the food web and
reduction in their population may impact
other species. For example, reduced
pollination because of absence of male
mosquitoes may affect plants and thus,
other species. Frogs and lizards which eat
mosquitoes may be affected, though in a
limited manner. This risk is higher for the
population suppression strategy.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison
MEDIUM RISK PROBABILITY
>
18
Glossary Ecosystem Humans Labs/Institutions Government
CREATE DEPLOY MONITOR
Risk 3b: Transfer of gene drive to other species
• Random sampling of other species should be performed to identify if there has been any transfer of gene drives.
Recommendations
Horizontal gene transfer is the transmission
of genomic fragments between organisms
other than that from parent to offspring.
Horizontal gene transfer has been widely
studied as the mechanism by which
antibiotic resistance spreads in bacteria.17
However, such gene transfers have been
reported across eukaryotes.18
The chances of this occurring are low;
however if such a transfer does happen, it
could be potentially devastating for other
species. Random sampling of other species
would need to be performed to identify if
such a transfer has occurred.
Risk Evidence Potential Mitigation
Gene drives may be passed onto other
mosquito species or in rare occasions
unrelated species. Most known cases of
such horizontal gene transfers have
occurred as a result of evolutionary
dynamics and hence, it is a likely risk with
the population replacement strategy where
the gene modification will remain in the
environment forever.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison
LOW RISK PROBABILITY
<
19
Glossary Ecosystem Humans Labs/Institutions Government
CREATE DEPLOY MONITOR
Risk 3c: Emergence of new species/increased population
of another species
• Mosquito populations should be closely monitored.
• For any significant change in population of any particular species, measures should be in place for population control.
• For state border areas, interstate bodies should agree on a single action plan for deploying GMMs.
Recommendations
Mosquito populations are known to
compete with each other over food
resources.19 It is thus likely, if the
population of one species is reduced, other
species population may increase. Further,
adaptation of other species to exploit the
available food resources may also occur.
Gene drive strategies which inhibit the
pathogen instead of reducing mosquito
populations may be preferred.
Risk Evidence Potential Mitigation
Development of resistance or change in
ecological balance may lead to the
emergence of a new mosquito species or
increased population of another species.
This may consequently cause an increase in
the incidence of other vector-borne
diseases. The probability of risk is higher in
population suppression because of resource
availability.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison
MEDIUM RISK PROBABILITY
>
20
Glossary Ecosystem Humans Labs/Institutions Government
CREATE DEPLOY MONITOR
Risk 3d: Transfer of infectious pathogen to another
vector
• Monitoring of disease incidence and mosquito population should be performed.
• If a decrease in mosquito population is not correlated by decrease in disease incidence, the possibility of a new vector-host relationship
should be researched.
Recommendations
Cross-species transmission of pathogens is
a well-studied phenomenon. Both bacteria
and viruses have been known to find new
hosts.20 Examples for cross-species
transmission include HIV, SARS, and
influenza. It is therefore reasonable to
conclude that it is probable for such a
cross-species vector transmission to occur
over time.
There is no way to prevent the transfer of
pathogen from happening; but if it does
occur, GMMs would have to be created
against the new vector.
Risk Evidence Potential Mitigation
In the absence of the existing vector, the
pathogen may move into another vector. If
this happens, the GMM will have no effect
on the disease incidence. The risk
probability for this happening is higher in
population suppression strategy because
the absence of the vector might force the
pathogen to find another vector.
Risk Description
Who will be
affected?
Who is
responsible?
Risk
comparison
LOW RISK PROBABILITY
>
21
Glossary Ecosystem Humans Labs/Institutions Government
For Monitoring Agencies: For Government:
MONITOR - Recommendations
Monitoring agencies should be in place for the
following parameters:
• GMM population
• Target mosquito population
• Population of other mosquito species
• Disease incidence
• Impacts on food chain
• Transfer of gene drive to other species
Government should form monitoring agencies and
prescribe standards to be followed by them.
Any changes in ecology or adverse events should be
reported to the government authority.
A redressal cell should be set up for addressing
concerns arising out of adverse events following GMM
use.
Liability of adverse events should be decided between
laboratory, deploying agency, monitoring agency and
governmental bodies before deployment.
22
Risk of
Unintended
Consequences
Other Ethical Considerations
Lab Trials on
Plants
GE of
Plants
GE of Human Cell
Lines/Tissues
GE of Human
EmbryosGE of Animals
Lab Trials of
Animals
Fundamental Research &
Development
Commercialisation
Commercial Research &
Development
Preclinical trials on Animals
Field Trials of
Plants
Field trials on Animals
Somatic Trials on Humans
Germline Trials on Humans
Sale of GE Plants
Sale of GE Animals
Commercialised
Treatment Therapy
Commercialised
Enhancement Therapy
Lab Trials on
Gene Drives
Field Trials on
Gene Drives
Deployment of
Gene Drives
Gene Drive – Risk Assessment
23
Maturity Stage Applicable to Group (as defined in analytical model)
Public
Trials
Create
Commercialisation
Commercial
R&D
Fundamental
R&D
Regulate
Test, publish,
monitor after
release to public
Approve
Technology intended for
commercialisation must meet standards
and submit proof of concept before
moving to open trials
Set Standards
Provided these are met, research can be freely conducted in
lab conditions. For GMM, exhaustive training for personnel
and containment measures should be enforced
Pyramidal Regulation
24
Summary of Recommendations
Research into GMMs should be
allowed in laboratories with
appropriate infrastructure and
containment facilities for
mosquitoes and pathogen.
Personnel with access to
mosquitoes/pathogens should
have adequate training and
adhere to GLP guidelines.
Deployment of mosquitoes
should be contingent on
absence of any significant
non-target mutations and
efficacy of GMM in laboratory
trials.
Selection of target areas for
trials or release should be
dependent on accurate data
about disease burden and
mosquito breeding hotspots.
Defined monitoring agencies
should be set up to determine
mosquito populations, disease
incidence and impacts on food
chain.
Public engagement and
dialogue should precede any
trials or deployment of GMMs.
Stage 1: Create GMM Stage 2: Deploy Stage 3: Monitor
25
1. https://www.healthissuesindia.com/infectious-diseases/
2. Laboratory Trials (Hammond et al., A CRISPR-Cas9 gene drive system targeting female reproduction in the malaria mosquito vector Anopheles gambiae. Nature Biotech 34, 78-83 2016)
and Field Trials: Oxitec – Cayman Islands, Brazil, India
3. Laboratory Trials (V.M. Gantz et al., “Highly efficient Cas9-mediated gene drive for population modification of the malaria vector mosquito Anopheles stephensi,” PNAS, 112:E6736-
E6743, 2015). No known field trials.
4. Schaefer KA, Wu W, Colgan DF, Tsang SH, Bassuk AG and Mahajan VB. Unexpected mutations after CRISPR–Cas9 editing in vivo. 2017 Nature Methods 14, 547–548
5. https://www.nature.com/articles/nmeth.4664?utm_source=newsletter&utm_medium=email&utm_campaign=newsletter_axiosscience&stream=science
6. Bull JJ. Lethal Gene Drive Selects Inbreeding. 2017 Evolution, Medicine, and Public Health 1, 1–16.
7 Unckless RL, Clark AG and Messer PW. Evolution of Resistance Against CRISPR/Cas9 Gene Drive. 2017 Genetics 205, 827-84
8 Tabashnik BE and Carriere Y. Field-Evolved Resistance to Bt Cotton: Bollworm in the U.S. and Pink Bollworm in India. 2010 Southwestern Entomologist 35, 417- 424.
9 https://www.businessinsider.in/Here-Are-5-Times-Infectious-Diseases-Escaped-From-Laboratory-Containment/articleshow/38442679.cms
10 http://www-naweb.iaea.org/nafa/ipc/public/guidelines-for-routine-colony-maintenance-of-Aedes-mosquito-species-v1.0.pdf
11 https://www.theguardian.com/world/2014/oct/07/india-dengue-fever-300-times-higher-reported-study
12 https://www.ft.com/content/0e87d150-be6d-11e3-a1bf-00144feabdc0
13 http://www.how2lab.com/leisure/mosquito.php
14 Dash AP, Adak T, Raghavendra K and Singh OP. The biology and control of malaria vectors in India. 2007 Current Science 92, 1571-1578
15 Singh P, Lingala M, Sarkar S and Dhiman RC. Mapping of Malaria Vectors at District Level in India: Changing Scenario and Identified Gaps. 2017 https://doi.org/10.1089/vbz.2016.2018
16 https://www.nature.com/news/2010/100721/full/466432a.html
17 Levy SB and Marshall B. Antibacterial resistance worldwide: causes, challenges and responses. 2004 Nature Medicine 10, S122–S129
18 Keeling PJ and Palmer JD. Horizontal gene transfer in eukaryotic evolution. 2008 Nature Reviews Genetics 9, 605–618
19 Juliano SA. Species introduction and replacement among mosquitoes: interspecific resource competition or apparent competition? 1998 Ecology 79, 255-268
20 Faria NR, Suchard MA, Rambaut A, Streicker DG and Lemey P. Simultaneously reconstructing viral cross-species transmission history and identifying the underlying constraints,
2013 Philos Trans R Soc Lond B Biol Sci, 368 (1614): 20120196
References
26

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Takshashila Discussion Slidedoc: Gene Drives in Infectious Diseases - A Risk Assessment

  • 1. A Risk Assessment of the Potential Use of Gene Drives in Infectious Diseases Shambhavi Naik 1
  • 2. Executive Summary Gene drives are being explored for alleviating vector-borne infectious diseases however, the risks of employing them need to be understood. This document assesses the potential use of gene drives in India by performing a stage-wise risk assessment of deploying gene drive. 2 Gene drive mosquitoes are an application of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology. The application is to develop mosquitoes that decrease the incidence of mosquito-borne diseases. Current research into engineering these mosquitoes is being funded by the Bill and Melinda Gates Foundation, Defense Advanced Research Projects Agency (DARPA) and more recently, the Tata Trusts. A British company, Oxitec has also been experimenting with CRISPR in Cayman Islands, Brazil and Maharashtra. Research into gene drives should be promoted however, there are risks associated with their potential use in India. Given the nature of the technology, it is recommended that robust monitoring mechanisms for disease incidence, mosquito burden and ecological impact be implemented before deploying these mosquitoes. Data driven decisions on identifying the type of gene drive and deployment locations will ensure effective use of the technology.
  • 3. Gene drives and infectious diseases • In India, infectious diseases have a high economic burden.1 • Gene drives refer to Gene Edited Mosquitoes (GMM) which can pass on their gene modification to future generations of mosquitoes. • Scientists are currently developing GMMs to help alleviate incidence of malaria and dengue, amongst other vector-borne diseases. • Given the economic burden of vector-borne infectious diseases in India, it is prudent to explore gene drive technology for eradicating the diseases. However, the technology is still in its nascent stages and an appropriate risk assessment is necessary to make an informed decision and initiate public dialogue over its use. 3
  • 4. Stage 1: CREATE GMM Stage 2: DEPLOY Stage 3: MONITOR 1. Choose target area for field trial 2. Evaluate disease burden/mosquito population prior to trial 3. Evaluate disease burden/mosquito population post trial 4. Calculate and deploy GMM based on incidence data and efficacy of GMM as evaluated through trials 1. Continued surveillance of GMMs and ecosystem to ensure early detection of any unintended consequences 1. Select the disease to target through GMM 2. Identify the pathogen strain(s) present locally causing the disease 3. Identify the local vector species 4. Choose the most effective GMM strategy to target the disease (see on Page 7) Steps and stages involved in using a gene drive 4
  • 5. Risk determination matrix Parameters Low Risk Medium Risk High Risk Ease of Mitigation Best practices available Best practices available Best practices not yet established Number of stakeholders involved (Ease of implementing mitigation measures) Only one (laboratory level) Multiple (Lab + governmental agencies) Multiple (Lab + governmental agencies) Probability of Occurrence Low Medium High 5
  • 6. Glossary Ecosystem – includes humans, animals and plants. Humans. Laboratory/Institution: The organisation (private or government) that will create the GMMs. Government: Governmental agencies (Local, State and Union) responsible for monitoring disease burden (National Vector Borne Disease Control Programme) and approving gene drive research and release. Key participants and their role in gene drive development and usage 6
  • 7. Stage 1: Create GMM GMMs are engineered in laboratories of either private or public institutions. The designated laboratory would have to demonstrate containment facilities that meet the required safety standards for the containment of mosquitoes and the pathogen under study. Trained personnel will be required to perform experiments and laboratory trials. There are two known strategies in designing the GMM: Population Suppression - Decrease fertility of mosquitoes2 This approach designs a modified male mosquito that upon mating with a wild-type female will result in an unviable offspring. Thus, over time, the mosquito population will decrease and subsequently, the gene drive will disappear. The disadvantage of this approach is that modified male mosquitoes will need to be released into the environment every season till the entire species is wiped out. Population Replacement - Reduce capability of GMM to carry pathogen3 This approach introduces an anti-pathogen peptide in the mosquito, so that it can no longer host the pathogen. So the mosquito species survives and continues to pass the modification to its offspring. The disadvantage of this approach is that the genetic modification will remain in the environment forever, increasing the likelihood of unintended consequences. 7
  • 8. CREATE DEPLOY MONITOR LOW RISK PROBABILITY Risk 1a: GMMs have non-target mutations • Submission of genetic sequencing data for GMM should be obligatory for deployment approval. Data should highlight any changes in gene sequences and resulting physiological changes in GMM. • Government approval to field trials and environmental release of the GMM should be contingent on demonstration of no other functional change than that described in the proposal. Recommendations In 2017, Schaefer et al4, reported the presence of unexpected mutations in mice edited using CRISPR. However, the paper was retracted5 in March 2018 following criticism that all mutations may not have been caused directly by CRISPR. The presence of non-target mutations is still being debated and hence, as a precaution, should be tested in GMMs. Laboratory should conduct exhaustive studies to identify non-target genetic changes through gene sequencing across GMM generations. Phenotypic changes in GMM as a result of the mutations should be documented. All non-target mutation data studies should be done prior to deployment of the GMM. Risk Evidence Potential Mitigation Gene editing can lead to non-target mutations which may have physiological effects. GMMs may become resistant to insecticide, may harbor other pathogens or may not be effective at preventing the disease they were designed against. Both population suppression and replacement approaches have similar potentials of carrying non-target mutations. Risk Description Who will be affected? Who is responsible? Risk comparison = Glossary Ecosystem Humans Labs/Institutions Government 8
  • 9. CREATE DEPLOY MONITOR LOW RISK PROBABILITYRisk 1b: GMM or pathogen becomes resistant to the genetic modification • Include a molecular marker to identify GMM for sampling. • Approval for deployment should be contingent on demonstration of resistance studies. A threshold for number of generations within which resistance may appear should be preset to avoid those GMMs which would be vulnerable to development of resistance quickly. • Ensure proper monitoring mechanisms are set to capture GMMs for sampling. Recommendations Scientific reports suggest that GMM created to lose viability may develop resistance to the modification.6,7 A similar selection-based resistance has been observed with the boll worm which developed resistance to the toxin secreted by BT cotton plants.8 Exhaustive studies must be conducted to assess when resistance develops across GMM generations. Equivalent resistance studies in pathogens would be difficult because of the requirement of human host for completion of life cycle. Monitoring mechanisms should be put in place to sample the deployed GMM for development of resistance. Risk Evidence Potential Mitigation GMM or pathogen may become resistant to the genetic modification. As species evolve, they may find a way to escape modifications if it does not provide a significant survival advantage. The population suppression approach may be susceptible to resistance development, since the approach is lethal to mosquitoes and evolution pressures will select for resistant mutations. Risk Description Who will be affected? Who is responsible? Risk comparison > 9 Glossary Ecosystem Humans Labs/Institutions Government
  • 10. CREATE DEPLOY MONITOR LOW RISK PROBABILITYRisk 1c: GMMs or pathogens escape from the Laboratory/Transport • Government approval for gene drive research should be contingent on demonstration of necessary infrastructure and Good Lab Practices (GLP) compliance. • Appropriate training for personnel working in laboratory or transport facilities and periodic assessment of the training should be obligatory. • Funding for gene drive research should include resources for developing and maintaining the infrastructure and best practices. Recommendations Pathogens have been known to escape from laboratories and infect individuals in the past.9 The main cause has been poor infrastructure and containment facilities. Escape of mosquitoes is also possible and the Food and Agriculture Organization of the United Nations has issued guidelines for colony maintenance of mosquitoes.10 Handling and containment of GMM and pathogens should follow best practices established worldwide. Access to GMM and pathogen should be restricted to trained personnel. Pathogen cultures should be maintained in GLP-compliant facilities under appropriate containment measures. Risk Evidence Potential Mitigation If experimental mosquitoes are released, they may influence the environment by mating with other mosquitoes. However, given the low number of GMM that may escape, their impact will be minimal. If the pathogen escapes, it may infect lab personnel and residents in the leak’s vicinity. However, given that the spread of the pathogen requires a vector, risk is low. Risk Description Who will be affected? Who is responsible? Risk comparison = 10 Glossary Ecosystem Humans Labs/Institutions Government
  • 11. Create GMM - Recommendations • Government should set standards for institutions wishing to conduct gene drive research. Such standards should include the demonstration of necessary infrastructure, GLP compliance and training of personnel. • Government should set standards for GMMs to be deployed in the environment. These should include the presence of a molecular marker for identification, absence of functional non-target mutations and minimum number of generations tested for resistance development. • Appropriate training for personnel working inside laboratory or transport facilities and periodic assessment of the training should be obligatory. • Funding proposals should include resources for developing and maintaining the infrastructure and best practices. • Laboratories wishing to do gene drive research should follow GLP guidelines and best practices as outlined by the government to ensure containment of mosquitoes and pathogens. For Laboratories: For Government: 11
  • 12. Stage 2: Deploy Once a GMM has been designed and tested under laboratory conditions, field trials would be conducted in select locations. Deployment of GMMs would be approved contingent upon satisfactory results from the field trials. 12
  • 13. CREATE DEPLOY MONITOR HIGH RISK PROBABILITYRisk 2a: GMMs get deployed at inappropriate spaces because of inaccurate burden data • The first step for GMM deployment would be to capture and validate accurate data on disease burden through improved reporting systems. • Data on hotpots for mosquito breeding sites would be necessary to ensure appropriate deployment of mosquitoes. • Analysis of these data to generate predictive models for forecasting breeding hotspots would be beneficial for identifying targets for GMM deployment. Recommendations Studies have reported that dengue incidences in India are nearly 300 times higher than official reports.11 The incidence of malaria has been inconsistent with WHO estimating 15,000 casualties/year, while other studies suggest a plausible casualty range between 125000 – 277000 people annually in India.12 Monitoring mechanisms should be set up to determine disease and mosquito burden before deploying GMMs. A comprehensive study report of the area to be targeted along with analysis of disease burden, mosquito burden and demographic studies should be performed before deploying GMMs. Risk Evidence Potential Mitigation Infectious disease burden has been underreported in official records and current inefficient mechanisms of reporting could lead to misidentification of disease hotspots. Absence of robust real- time/predictive data could lead to deployment of GMMs in incorrect spots thereby reducing their efficiency to combat the disease. Risk Description Who will be affected? Who is responsible? Risk comparison = 13 Glossary Ecosystem Humans Labs/Institutions Government
  • 14. CREATE DEPLOY MONITOR HIGH RISK PROBABILITYRisk 2b: Migration of mosquitoes affects efficacy of GMMs • Constant monitoring of mosquito populations to identify any changes. • For any significant change in population of any particular species, measures should be put in place for population control. • For state border areas, interstate bodies should agree on a single action plan for deploying GMMs. Recommendations Mosquitoes generally live in the vicinity of their breeding sites – travelling roughly 50 – 100 meters. However, they can travel further in search of food resources. Some mosquito species have been known to travel as far as 100-150 km.13 Stronger reporting systems would facilitate data-based deployment of GMMs. Migration may be combated by increasing the deployment of GMMs. Interstate cooperation would be required, particularly in the border areas to ensure efficient use of GMMs. Risk Evidence Potential Mitigation India has favourable weather for mosquito breeding. Expanding city limits provide additional breeding sites. Thus, it is likely that deployment of GMMs may be hampered by migration of mosquitoes from adjoining areas. This is particularly true in population suppression strategy where the availability of food resources may act as an added attractant. Risk Description Who will be affected? Who is responsible? Risk comparison > 14 Glossary Ecosystem Humans Labs/Institutions Government
  • 15. CREATE DEPLOY MONITOR MEDIUM RISK PROBABILITYRisk 2c: Spread of mosquitoes/pathogens across the country would affect the efficacy of GMMs • Mosquito populations must be constantly monitored to identify changes. • GMM deployment should be done concomitant with ongoing measures for mosquito control. • Government should take expert opinion before approving field trials to prevent overlap of GMMs from different sources. Recommendations For example, there are six primary vectors (Anopheles culicifacies, An. dirus, An. fluviatilis, An. minimus, An. sundaicus and An. stephensi) for malaria in India and five of them operate in species complexes.14 Their distribution across India is variable and needs to be studied locally to define the GMM strategy.15 A targeted approach identifying the disease and vector spectrum to be used for GMM has to be identified. Risk Evidence Potential Mitigation India is home to a wide spread of disease- causing mosquitoes and pathogens. Even for a single pathogen there are various existing vectors. Hence, even if one mosquito species is targeted, the pathogen may just proliferate in another vector species. Thus, for GMM strategy to work, all vector species for a target pathogen species would need to be modified. Risk Description Who will be affected? Who is responsible? Risk comparison = 15 Glossary Ecosystem Humans Labs/Institutions Government
  • 16. For Deploying Agency: For Government: Deploy - Recommendations • Target areas for deployment/field trials should be based on evidence of mosquito breeding hotspots. Mosquito population/disease incidence should be measured for at least 3 years before deployment and 3 years post deployment. • Sampling of mosquito populations/disease incidence should be performed according to government prescribed standards. • Any changes in mosquito populations or disease incidence should be immediately reported to the designated governmental authority and laboratory. • Guidelines and best practices for measuring mosquito populations/disease incidence should be prescribed. • Field trial/deployment approval should be given by a committee of scientists, ecologists and citizens. • Awareness about GMMs and public engagement over their possible effects should be created before field trials. Representatives from both the laboratory and deploying agency should be present for such engagement. 16
  • 17. Stage 3: Monitor Post deployment of mosquitoes, the ecosystem should be continuously monitored for changes in disease incidence, mosquito populations and food chain impacts. 17
  • 18. CREATE DEPLOY MONITOR Risk 3a: GMM have a negative impact on the food chain • Mathematical modelling and field testing should be done to simulate the impact of population loss on the food chain. • Identification of species dependent on mosquitoes in the area of deployment should be made and their populations should be monitored for changes. Recommendations There is considerable debate on how important mosquitoes are in the food chain. Male mosquitoes are not primary pollinators of crops required for human consumption. Predators may also quickly find other insects to fill up their diet. However, specialised predators like the mosquitofish may be severely impacted.16 Mathematical and field testing should be done to simulate the impact of population loss on the food chain. Gene drive strategies which inhibit the pathogen instead of reducing mosquito populations may be preferred. Risk Evidence Potential Mitigation Mosquitoes are a part of the food web and reduction in their population may impact other species. For example, reduced pollination because of absence of male mosquitoes may affect plants and thus, other species. Frogs and lizards which eat mosquitoes may be affected, though in a limited manner. This risk is higher for the population suppression strategy. Risk Description Who will be affected? Who is responsible? Risk comparison MEDIUM RISK PROBABILITY > 18 Glossary Ecosystem Humans Labs/Institutions Government
  • 19. CREATE DEPLOY MONITOR Risk 3b: Transfer of gene drive to other species • Random sampling of other species should be performed to identify if there has been any transfer of gene drives. Recommendations Horizontal gene transfer is the transmission of genomic fragments between organisms other than that from parent to offspring. Horizontal gene transfer has been widely studied as the mechanism by which antibiotic resistance spreads in bacteria.17 However, such gene transfers have been reported across eukaryotes.18 The chances of this occurring are low; however if such a transfer does happen, it could be potentially devastating for other species. Random sampling of other species would need to be performed to identify if such a transfer has occurred. Risk Evidence Potential Mitigation Gene drives may be passed onto other mosquito species or in rare occasions unrelated species. Most known cases of such horizontal gene transfers have occurred as a result of evolutionary dynamics and hence, it is a likely risk with the population replacement strategy where the gene modification will remain in the environment forever. Risk Description Who will be affected? Who is responsible? Risk comparison LOW RISK PROBABILITY < 19 Glossary Ecosystem Humans Labs/Institutions Government
  • 20. CREATE DEPLOY MONITOR Risk 3c: Emergence of new species/increased population of another species • Mosquito populations should be closely monitored. • For any significant change in population of any particular species, measures should be in place for population control. • For state border areas, interstate bodies should agree on a single action plan for deploying GMMs. Recommendations Mosquito populations are known to compete with each other over food resources.19 It is thus likely, if the population of one species is reduced, other species population may increase. Further, adaptation of other species to exploit the available food resources may also occur. Gene drive strategies which inhibit the pathogen instead of reducing mosquito populations may be preferred. Risk Evidence Potential Mitigation Development of resistance or change in ecological balance may lead to the emergence of a new mosquito species or increased population of another species. This may consequently cause an increase in the incidence of other vector-borne diseases. The probability of risk is higher in population suppression because of resource availability. Risk Description Who will be affected? Who is responsible? Risk comparison MEDIUM RISK PROBABILITY > 20 Glossary Ecosystem Humans Labs/Institutions Government
  • 21. CREATE DEPLOY MONITOR Risk 3d: Transfer of infectious pathogen to another vector • Monitoring of disease incidence and mosquito population should be performed. • If a decrease in mosquito population is not correlated by decrease in disease incidence, the possibility of a new vector-host relationship should be researched. Recommendations Cross-species transmission of pathogens is a well-studied phenomenon. Both bacteria and viruses have been known to find new hosts.20 Examples for cross-species transmission include HIV, SARS, and influenza. It is therefore reasonable to conclude that it is probable for such a cross-species vector transmission to occur over time. There is no way to prevent the transfer of pathogen from happening; but if it does occur, GMMs would have to be created against the new vector. Risk Evidence Potential Mitigation In the absence of the existing vector, the pathogen may move into another vector. If this happens, the GMM will have no effect on the disease incidence. The risk probability for this happening is higher in population suppression strategy because the absence of the vector might force the pathogen to find another vector. Risk Description Who will be affected? Who is responsible? Risk comparison LOW RISK PROBABILITY > 21 Glossary Ecosystem Humans Labs/Institutions Government
  • 22. For Monitoring Agencies: For Government: MONITOR - Recommendations Monitoring agencies should be in place for the following parameters: • GMM population • Target mosquito population • Population of other mosquito species • Disease incidence • Impacts on food chain • Transfer of gene drive to other species Government should form monitoring agencies and prescribe standards to be followed by them. Any changes in ecology or adverse events should be reported to the government authority. A redressal cell should be set up for addressing concerns arising out of adverse events following GMM use. Liability of adverse events should be decided between laboratory, deploying agency, monitoring agency and governmental bodies before deployment. 22
  • 23. Risk of Unintended Consequences Other Ethical Considerations Lab Trials on Plants GE of Plants GE of Human Cell Lines/Tissues GE of Human EmbryosGE of Animals Lab Trials of Animals Fundamental Research & Development Commercialisation Commercial Research & Development Preclinical trials on Animals Field Trials of Plants Field trials on Animals Somatic Trials on Humans Germline Trials on Humans Sale of GE Plants Sale of GE Animals Commercialised Treatment Therapy Commercialised Enhancement Therapy Lab Trials on Gene Drives Field Trials on Gene Drives Deployment of Gene Drives Gene Drive – Risk Assessment 23
  • 24. Maturity Stage Applicable to Group (as defined in analytical model) Public Trials Create Commercialisation Commercial R&D Fundamental R&D Regulate Test, publish, monitor after release to public Approve Technology intended for commercialisation must meet standards and submit proof of concept before moving to open trials Set Standards Provided these are met, research can be freely conducted in lab conditions. For GMM, exhaustive training for personnel and containment measures should be enforced Pyramidal Regulation 24
  • 25. Summary of Recommendations Research into GMMs should be allowed in laboratories with appropriate infrastructure and containment facilities for mosquitoes and pathogen. Personnel with access to mosquitoes/pathogens should have adequate training and adhere to GLP guidelines. Deployment of mosquitoes should be contingent on absence of any significant non-target mutations and efficacy of GMM in laboratory trials. Selection of target areas for trials or release should be dependent on accurate data about disease burden and mosquito breeding hotspots. Defined monitoring agencies should be set up to determine mosquito populations, disease incidence and impacts on food chain. Public engagement and dialogue should precede any trials or deployment of GMMs. Stage 1: Create GMM Stage 2: Deploy Stage 3: Monitor 25
  • 26. 1. https://www.healthissuesindia.com/infectious-diseases/ 2. Laboratory Trials (Hammond et al., A CRISPR-Cas9 gene drive system targeting female reproduction in the malaria mosquito vector Anopheles gambiae. Nature Biotech 34, 78-83 2016) and Field Trials: Oxitec – Cayman Islands, Brazil, India 3. Laboratory Trials (V.M. Gantz et al., “Highly efficient Cas9-mediated gene drive for population modification of the malaria vector mosquito Anopheles stephensi,” PNAS, 112:E6736- E6743, 2015). No known field trials. 4. Schaefer KA, Wu W, Colgan DF, Tsang SH, Bassuk AG and Mahajan VB. Unexpected mutations after CRISPR–Cas9 editing in vivo. 2017 Nature Methods 14, 547–548 5. https://www.nature.com/articles/nmeth.4664?utm_source=newsletter&utm_medium=email&utm_campaign=newsletter_axiosscience&stream=science 6. Bull JJ. Lethal Gene Drive Selects Inbreeding. 2017 Evolution, Medicine, and Public Health 1, 1–16. 7 Unckless RL, Clark AG and Messer PW. Evolution of Resistance Against CRISPR/Cas9 Gene Drive. 2017 Genetics 205, 827-84 8 Tabashnik BE and Carriere Y. Field-Evolved Resistance to Bt Cotton: Bollworm in the U.S. and Pink Bollworm in India. 2010 Southwestern Entomologist 35, 417- 424. 9 https://www.businessinsider.in/Here-Are-5-Times-Infectious-Diseases-Escaped-From-Laboratory-Containment/articleshow/38442679.cms 10 http://www-naweb.iaea.org/nafa/ipc/public/guidelines-for-routine-colony-maintenance-of-Aedes-mosquito-species-v1.0.pdf 11 https://www.theguardian.com/world/2014/oct/07/india-dengue-fever-300-times-higher-reported-study 12 https://www.ft.com/content/0e87d150-be6d-11e3-a1bf-00144feabdc0 13 http://www.how2lab.com/leisure/mosquito.php 14 Dash AP, Adak T, Raghavendra K and Singh OP. The biology and control of malaria vectors in India. 2007 Current Science 92, 1571-1578 15 Singh P, Lingala M, Sarkar S and Dhiman RC. Mapping of Malaria Vectors at District Level in India: Changing Scenario and Identified Gaps. 2017 https://doi.org/10.1089/vbz.2016.2018 16 https://www.nature.com/news/2010/100721/full/466432a.html 17 Levy SB and Marshall B. Antibacterial resistance worldwide: causes, challenges and responses. 2004 Nature Medicine 10, S122–S129 18 Keeling PJ and Palmer JD. Horizontal gene transfer in eukaryotic evolution. 2008 Nature Reviews Genetics 9, 605–618 19 Juliano SA. Species introduction and replacement among mosquitoes: interspecific resource competition or apparent competition? 1998 Ecology 79, 255-268 20 Faria NR, Suchard MA, Rambaut A, Streicker DG and Lemey P. Simultaneously reconstructing viral cross-species transmission history and identifying the underlying constraints, 2013 Philos Trans R Soc Lond B Biol Sci, 368 (1614): 20120196 References 26