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„Limits of Concern for the risk assessment of GMP”
2
Federal Agency for Nature Conservation, Unit II 3.3. (Risk
Assessment GMO)
UFOPLAN 2013 (testing & development project)
October 2013 – June 2017
Aims of the project:
evaluation
operationalisation
exemplification
„Limits of Concern for the risk assessment of GMP”
3
LoCs and protection goals
Role of LoCs in the stepwise testing approach
Relationship between the comparative safety assessment
and LoCs
LoCs and long-term effects
LoCs for certain areas of risk
LoC values for non-target organisms practicable and
reasonable
LoCs for species of conservation concern
„Limits of Concern for the risk assessment of GMP”
4
Literature / background information
Stakeholders interviews
Topic-related workshops with scientific experts
Stakeholder-Workshop
2 scientific publications Dolezel et al. (2017). Are Limits of Concern a useful concept to
improve the environmental risk assessment of GM plants? Environ Sci Eur (2017) 29:7; doi 10.1186/s12302-017-0104-2
Final report
public presentation
Background
6
„…the level of environmental protection to be preserved is expressed through the setting of limits of concern…“
Background
7
natural resources or natural resource services
EU legislation
thresholds for acceptable adverse effect(s) for ERA purposes
Background
8
ERA of applicants:
stat. sign. difference ≠ biological relevance
qualitative risk characterisation: negligible/not likely
EFSA objectives:
stat. sign. differences = biological relevance ?
quantitative risk characterisation: effect size = LoC ?
Definition LoC (EFSA 2010)
9
“…the minimum ecological effects that are
deemed biologically relevant and that
are deemed of sufficient magnitude to
cause harm”
Operationalization of the LoC concept (EFSA 2010)
11
protection goals relevant for the ERA
protection goals in the EU
assessment endpoints
measurement endpoints
Limit of Concern
Abundance? Mortality? Weight? …
Open questions & challenges I
12
Lack of harm definition for PGs
In ERA: damage to PGs cannot be tested directly – use of
proxies
Ecological entities assessed ≠ protected entities
Spatial & temporal scales
Lack of scientific knowledge on ecological significance of
adverse effects
consequence for definition of LoC
14
Open questions & challenges II
What shall a LoC constitute (trigger value, stop criterion)?
What is the consequence of an exceedance/non-
exceedance?
16
Open questions & challenges III
Stat. sign. differences or non-equivalences need to be
followed up (EFSA 2010)
Assessment of their toxicological or biological relevance
taking safety limits into account (EFSA 2010)
Results of comparative assessment may be relevant for LoC
concept
But usually not done in ERA practice
Example GM soybean & lectins – effects on NTOs
18
Open questions & challenges IV
LoCs should be derived from
EU-wide protection goals
and should be valid for all
receiving environments
20
Open questions & challenges V
Define LoCs if long-term effects are likely to occur and if
risk hypothesis can be formulated
Requires risk management measures and post-market
environmental monitoring
21
LoC Definition
Acceptability threshold (quantitatively, qualitatively) for
adverse effects on entities, functions, processes …
…that trigger regulatory concern …
… that have the possibility to cause harm to the relevant protection
goal(s) (EFSA 2010)
… or because these adverse effects are valued as being important for a
specific protection goal (see EFSA SC 2011)
22
Operationalisation of LoCs
3 Examples (risk areas):
Outcrossing, persistence, invasiveness (HT oilseed rape)
Impacts on NTOs (Bt maize)
Effects due to changes in cultivation & management
methods (HT crops)
23
Operationalisation of LoCs
3 Examples (risk areas):
Specific protection goals
Indicators to assess effects (based on Kowarik et al. 2008)
Existing thresholds
Aspects to consider for setting LoC
Dolezel et al. (20xx): in prep.
24
Definition of LoCs - Example Bt maize
effect/risk
effect/risk
GM pollen
possible starting point for LoCs
reduction in population size of faunal species
toxic effects on test species
exposure
25
Example: Bt Maize – NT Lepidoptera
biodiversity and agricultural protection goals
Proposals for LoCs
LoCs for lab studies: validation of thresholds needed
LoCs for field studies: effects on less mobile larval stages
exposure-based LoCs: amount of pollen deposited on field margins
differentiation of LoCs between in-crop and off-crop (see PPPs)
EFSA opinions (2011, 2012, 2015, 2016)
Ecosystem service concept for ERA (EFSA SC 2016)
negligible effects for NT Lepidoptera
Example: Bt Maize – NT Lepidoptera
• ERA of Bt maize (MON810, Bt11, 1507)
Source Protection object Protection levels
EFSA (2011, 2012) NT lepi in within maize fields & margins < 1 % global larval mortality
EFSA (2011, 2012) NT lepi of conservation concern in protected habitats
< 0,5 % local larval mortality
EFSA (2015) NT lepi of conservation concern in protected habitats
< 0,5-1 % larval mortality
EFSA SC (2016) Lepi as service providing unit for ES < 1 % reduction in abundance < 1 % global mortality
26
27
Example: Bt Maize – NT Lepidoptera
• dose-response relationships for Lepi larvae and Bt maize pollen (e.g. Holst et al. 2013, EFSA 2011)
• realistic pollen deposition data on food plants (e.g. Hofmann et al. 2016)
28
Conclusions
LoC – useful concept for ERA of GMOs
Further elaboration and specifications
LoC = scientific & political decision
Potential overlap with ES concept
Lack of scientific knowledge should not prevent defining LoCs
Enables harmonization between ERAs of different stressors
Decisions on exceedances of LoC before concept is applied
Transparency
Increased confidence in conclusions of risk
29
Marion Dolezel
Landuse & Biosafety
Environment Agency Austria
Tel.: +43-(0)1-31304 3120
Email: marion.dolezel@umweltbundesamt.at
www.umweltbundesamt.at
dsRNA & miRNA pathways Baseline information to support the risk assessment of RNAi-based GM plants
Petr Svoboda Institute of Molecular Genetics AS CR, Prague
A U C G A U C G A U C G
A U C G A U C G A U
RNA replication
RNA basepairing
Complementarity in nucleic acids
A U C G A U C G A U C G
A U C G A U C G
Sources & types of dsRNA
Exogenous
viral life cycle
inverted repeats convergent transcription pairing in trans
Endogenous
• frequently associated with parasitic mobile elements
genome
dsRNA response
adenosine deamination
interferon response
innate immunity
SEQUENCE-INDEPENDENT
RNAi innate immunity genome defense
SEQUENCE-SPECIFIC
dsRNA
dsRBD
dsRNA binding domain
other e.g. Staufen-mediated decay
The principle of RNA silencing
substrate
AGO
Dicer small RNA production
targeting
silencing (function)
RdRP
AGO
RdRP
amplificiation
uninjected parent not stained
antisense injected m
ex-3
in
situ
hyb
rid
iza
tio
n
dsRNA injected
Canonical animal RNAi pathway
RdRP
Dicer
AGO
AGO
AAAAA
mRNA cleavage
siRNA
dsRNA
siRNA
dsRBP
aberrant RNA
AGO
dicing
slicing
RISC
loading
substrate synthesis
viruses, convergent transcription, inverted repeat transcription, RdRp activity, artificial
Canonical animal RNAi pathway
• defense against elements (viruses, TEs) producing dsRNA • with or without RdRP amplification loop
RNAi: long dsRNA-induced sequence-specific mRNA degradation
dicing
repression
RISC (miRISC)
loading miRNA
Dicer
AGO
AAAAA
inhibition of translation mRNA degradation
GW182
pre-miRNA
dsRBP
AGO
Drosha
pri-miRNA pre-miRNA
DGCR8
Microprocessor complex
EXP5
mRNA degradation
RELOCATION TO P-BODIES
nucleus
cytoplasm
Canonical animal miRNA pathway
DGCR8
• post-transcriptional regulation of gene expression • stoichiometry (miRNA abundance/cell) matters
miRNA: regulatory RNAs produced by Dicer from genome-encoded small hairpin precursors
Dicer
RNaseIIIa “platform”
(DUF283)
RNaseIIIb
PAZ
DEXD
HELICc
NSMB 2012 19(4):436-40.
Dicer
• Dicer makes small RNAs
Argonaute-mediated silencing effects AGO
AGO2
AAAAA
mRNA cleavage by AGO2
Eukaryots
“miRNA-like” mRNA degradation
P-BODIES
CCR4-NOT
AGO
AAAAA
Inhibition of translation/deadenylation
GW182
Eukaryots
“RNAi-like”
RdDM
DNA methylation
Plants
other transcriptional silencing
heterochromatin
e.g. S. pombe … poorly understood in animals
POST-TRANSCRIPTIONAL
TRANSCRIPTIONAL
Argonaute structure and function AGO
PIWI
PAZ
N MID
mRNA
siRNA 3’
5’ 5’ 3’
• Argonaute structure explains principles of target recognition and repression
Argonaute structure and function AGO
PIWI
PAZ
N MID
mRNA
siRNA 3’
5’ 5’ 3’
• Dissociation constants for seed matching targets are in a pM range • low abundant miRNAs unlikely to have significant regulatory effects • seed match + abundance = siRNA off-targeting
Argonaute-mediated silencing effects AGO
Parameters influencing silencing by small RNAs
• small RNA abundance (stoichiometry)
• target site accessibility
• complementarity with the target
• type of silencing (transcriptional/post-transcriptional)
A small RNA seed sequence defines the minimal sequence complementarity required for silencing
nucleus cytoplasm
Ago
Class 2 hairpin
(miRNA-like) Class1 hairpin
(shRNA)
siRNA
EXPRESSION VECTOR
.
TRANSFECTION
Ago2
AAAAA Cleavage of
mRNA by Ago2
Ago
AAAAA
mRNA degradation Inhibition of translation
RELOCATION TO
P-BODIES
RISC
loading
short RNAs
(miRNAs and siRNAs)
Argonaute – targeting & off-targeting AGO
• off-targeting is siRNA-specific • any siRNA has off-targeting potential
Jackson et al. (2003) Nature Biotech
Argonaute – targeting & off-targeting AGO
Argonaute – targeting & off-targeting AGO
Jackson et al. (2003) Nature Biotech
• off-targeting is largely concentration-dependent • it is strongly reduced in sub-nanomolar range
transfected at 100nM
Pooling reduces off-target effects without affecting effciency
siRNA2 siRNA4 siRNA3 siRNA1 pool
Thermofisher/Dharmacom website
Argonaute – targeting & off-targeting AGO
• siRNA pooling is a way to reduce concentrations of individual siRNAs while keeping the constant siRNA amount in a transfection
• natural siRNA pools produced from siRNAs are highly specific because of a highly diluted off-targeting effect
Argonaute – targeting & off-targeting AGO
• off-targeting potential stems from seed sequence frequency • siRNA knock-downs - usually employ nM concentrations • hydrodynamic transfection (40 mg/mouse – Nature, 418, 38-39)
Ago
AAAAA
miRNA-like Inhibition
of translation
seed = nucleotides 2-7
Ago2
AAAAA
RNAi-like Cleavage of
mRNA by Ago2
seed = nucleotides 2-7
mRNA degradation
RNAi
Dicer
Co-existence of miRNA & RNAi pathways
defense gene control
inhibition of translation
miRNA
Dicer
AGO AGO
Arthropod set up
mRNA degradation
RNAi
Co-existence of miRNA & RNAi pathways
defense gene control
inhibition of translation
miRNA
AGO
Dicer
Annelida set up (some Molluscs?)
mRNA degradation
RNAi
defense gene control
inhibition of translation
miRNA
AGO
Dicer
interferon response
PKR
Co-existence of miRNA & RNAi pathways
defense
Vertebrate set up
mRNA degradation
RNAi
Co-existence of miRNA & RNAi pathways
defense gene control
inhibition of translation
miRNA
AGO
Dicer
RdRP Nematode set up (some Molluscs?)
Nematodes
endoRNAi antiviral defense replication
dsRNA dsRNA
DRH-1
Dicer
gene control
ERGO-1
AAAAA
mRNA cleavage
RdRP
WAGOs
RDE-4
1o siRNA
1o siRNA 26G RNA
22G RNA
DRH-3
2o siRNA
Dicer
immunity
RDE-1
AAAAA
mRNA cleavage
RdRP
SAGO-2
RDE-4
1o siRNA
22G RNA
DRH-3
2o siRNA
ERI
ERI
RDE-8
1o siRNA 22-23 nt
RNA clearance
exoRNAi
RDE-1
AAAAA
mRNA cleavage
RDE-8
RdRP
WAGOs
dsRNA
injection feeding soaking
1o siRNA
1o siRNA 22-23 nt
22G RNA
DRH-3
2o siRNA
DRH-1
Dicer RDE-4
nucleus
cytoplasm
Dicer
ALG-1/2
gene control
AGO
AAAAA
inhibition of translation
AIN-1
pre-miRNA
miRNA
miRNA 22-23 nt
pri-miRNA
Microprocessor complex
Nematodes
RNA clearance
exoRNAi
RDE-1
AAAAA
mRNA cleavage
RDE-8
RdRP
WAGOs
dsRNA
injection feeding soaking
1o siRNA
1o siRNA 22-23 nt
22G RNA
DRH-3
2o siRNA
DRH-1
Dicer RDE-4
0.5 - 1.0x106 dsRNA molecules per each gonad arm
Tabara et al., 1998
Plants
RDR6
RNA clearance (post-transcriptional)
transgene & viral silencing
AGO
dsRNA
viral long hairpin
21/22 nt siRNA
SDE3
sense RNA
RDR6 SGS3
DCL4/2 DCL3
AGO4/6
24 nt siRNA
RdDM AGO
SDE3
DNA methylation (transcriptional)
HEN1 HEN1 DRB3 DRB4
sense RNA
TAS loci
AGO miRNA
RDR6
DCL4
AGO1/7
tasiRNA
21nt tasiRNA
Gene regulation during development
HEN1 DRB
miRNA pathway in plants & animals
gene control
Plants
mRNA cleavage inhibition of translation
pre-miRNA
HYL1
AGO1 miRNA 21 nt
pri-miRNA
SE
HYL1 SE DC
L1
DC
L1
AGO1
AAAAA
SUO
HEN1 HEN1
nucleus cytoplasm
nucleus cytoplasm
Arthropods
AGO1
gene control
AGO1
AAAAA
inhibition of translation
GW182
LOQS
miRNA 21-23 nt
Dicer-1
nucleus cytoplasm
Mammals
AGO1-4
gene control
AGO1-4
AAAAA
inhibition of translation
GW182
TARBP2
miRNA 21-23 nt
Dicer-1
pre-miRNA
pri-miRNA
pre-miRNA
pri-miRNA
DGCR8
DGCR8
Drosha DGCR8
DGCR8
Drosha
Plants
AGO1
DCL2 DCL3
AGO10 AGO7
DCL1
miR-390 miR-156/166 U U A A
AGO2
MAIN miRNA PATHWAY
AGO4/6/9
21 nt 24 nt
long inverted repeats (evolving miRNAs)
ALTERNATIVE miRNA PATHWAY
DCL4
• highly complex RNA silencing system 4x Dicer, 10-20 Argonautes • a number of small RNAs, TGS & PTGS effects
Plants – transcriptional silencing
Canonical RdDM Non-canonical RdDM
• highly complex RNA silencing – crosstalks & redundancy
RNAi mobility - systemic RNAi
dsRNA
dsRNA
dsRNA
dsRNA delivery RNAi effect
Cell autonomous RNAi
Systemic RNAi
Environmental RNAi
dsRNA
Example
0.5 - 1.0x106 dsRNA molecules per each gonad arm
mammals
C. elegans some Arthropods (Tribolium) plants
C. elegans insects
Plants –> Animals
? ?
?
environmental & systemic RNAi
circulating miRNAs ?
?
Huang et al., 2006
Baum et al., 2007 Mao et al. 2007
environmental & systemic RNAi
Plants –> Animals
Unclear/controversial issues: Mechanism of transport • Mechanism of transport across membranes not explained • Unclear if free or bound to a protein • Survival in digestive tract? Effector complex structure • Would require binding of methylated single stranded RNAs by AGO Targeting stoichiometry • Concentrations estimated 68-250 fM – too low • Authors calculate ~850 molecules per cell, cannot be verified – data not released
Plants –> Animals
• meta-study of xenomiRs of 824 datasets from human tissues and body fluids • xenomiRs commonly present in tissues (17%) and body fluids (69%), • low abundance, 0.001% of host human miRNA counts • no significant enrichment in sequencing data from tissues and body fluids exposed
to dietary intake (e.g. liver). • no significant depletion in tissues and body fluids that are relatively separated
from the main bloodstream (e.g, brain and cerebro-spinal fluids) • the majority (81%) of body fluid xenomiRs stem from rodents, which are rare
human dietary contributions, but common laboratory animals. • body fluid samples from the same studies are clustered by xenomiR compositions
- suggesting technical batch effects. • feeding studies - no transfer of plant miRNAs into rat blood, or bovine milk
sequences into piglet blood.
doi: 10.1261/rna.059725.116
RNA, advanced online, Jan 6., 2017
Key points
• a targeting repertoire of a small RNA is largely determined by its seed – nucleotides 2-8. • not absolute rule (non-canonical binding) • allows some predictability, especially for conserved targets
• RNAi-like cleavage or miRNA-like target repression silencing effects are primarily defined by AGO isoform and basepairing
• targeting efficiency is determined by: • small RNA abundance (stoichiometry) • target site accessibility • complementarity with the target
• vertebrates have lack systemic RNAi, an RdRP amplification system, and highly processive Dicer -> inefficient RNAi
• plant small RNA pathways use 3’ end 2-O-methyl modification of all small RNAs. In mammals, such modification is found only in piRNAs bound to PIWI AGO cladein the germline
Sequence-specific RNA silencing
nucleus cytoplasm
GW182 AGO2
AAAAA
Cleavage of mRNA by Ago2
Exportin 5-mediated transport
AGO
AAAAA
mRNA degradation Inhibition of translation
relocation to P-bodies
GW182
miRNA duplex
Dicer
GW182 AGO
RISC loading
Mammalian microRNA pathway
pri-miRNA pre-miRNA
DGCR8
Microprocessor complex
DGCR8
Dicer cleavage
targeting
pre-miRNA
Drosha
miRISC
Animal Dicer evolution
• RNAi-dedicated Dicer-2 in Arthropods is a derived character
• the mammalian “miRNA” Dicer is related to miRNA-producing Dicer-1 in Arthropods
• Dicer in C. elegans produces efficiently miRNAs and siRNAs
Dicer
“miRNA” Dicer
mRNA degradation
RNAi
Dicer
Co-existence of miRNA & RNAi pathways
defense gene control
inhibition of translation
miRNA
Dicer
AGO AGO
mRNA degradation
RNAi
Co-existence of miRNA & RNAi pathways
defense gene control
inhibition of translation
miRNA
AGO
Dicer
mRNA degradation
RNAi
defense gene control
inhibition of translation
miRNA
AGO
Dicer
interferon response
PKR
Co-existence of miRNA & RNAi pathways
defense
Interferon response induced by long dsRNA (>30bp)
sensing
specific responses
MDA5 TLR3
PKR OAS
RIG-I
common response
INTERFERON RESPONSE
ISG interferon-stimulated genes
eIF2a P
RNaseL
global inhibition of translation
global mRNA degradation
2’,5’-OA
• The interferon response can be detected/monitored
Small RNA pathways in animals
mammals birds fish
Arthropoda
Nematoda
Annelida
Mollusca
Cnidaria
Porifera
Chordata
ECDYSOZOA
LOPHOTROCHOZOA
Chelicerata Myriapoda Crustacea Hexapoda
Trilobita †
Mammals (and vertebrates in general)
OAS
MDA5
TLR3
PACT
Dicer
miRNA RNAi
AGO1-4
gene control
AGO1-4
AAAAA
inhibition of translation
GW182
AGO2
AAAAA
mRNA cleavage
pre-miRNA
miRNA
dsRNA
siRNA
TARBP2 PKR
OAS
RIG-I
translational repression
RNAse L
IFN signaling
interferons &
interferon stimulated genes
Interferon response
common sensors
RNA silencing
antiviral defense
dsRNA
• miRNA pathway is the main RNA silencing pathway • main dsRNA response = sequence-independent interferon response
Annelids
Dicer
miRNA RNAi
AGO
AGO
AAAAA
inhibition of translation
AGO
AAAAA
mRNA cleavage
pre-miRNA
miRNA
dsRNA
siRNA
TARBP2 ?
OAS
RIG-I ?
MDA5 ?
RNAse L
signaling
innate immunity?
dsRNA response
common sensors
RNA silencing
dsRNA
?
?
• almost no functional data, set-up seems similar to mammals
Molluscs
RdRP
Dicer
miRNA RNAi
AGO
gene control & antiviral defense?
AGO
AAAAA
inhibition of translation
GW182
AGO
AAAAA
mRNA cleavage
pre-miRNA
miRNA
dsRNA
siRNA
TARBP2 PKR
OAS
RIG-I
MDA5
translational repression
RNAse L
IFN signaling
interferons &
interferon stimulated genes
Interferon response
common sensors
RNA silencing
antiviral defense
dsRNA
? MX
• almost no functional data, set-up seems similar to mammals • possible RdRP loop – would make it similar to nematodes
Arthropods
nucleus
cytoplasm
AGO2
defense gene control
AGO2
AAAAA
mRNA cleavage
siRNA
dsRNA
PKR
RIG-I
MDA5
Interferon response
common sensors
RNAi
dsRNA
AGO1
gene control
AGO1
AAAAA
inhibition of translation
GW182
pre-miRNA
LOQS
miRNA
miRNA 21-23 nt
pri-miRNA
Microprocessor
R2D2
Dicer-1
Dicer-2
TLR3?
signaling
innate immunity?
• separated miRNA & RNAi • sensors of the interferon response present
Nematodes
C. elegans is an outstanding model for analyzing RNA silencing • highly complex RNA silencing system • one Dicer but 26 Argonautes and 3 RdRPs • four pathways can be recognized
• miRNA • exoRNAi • endoRNAi • antiviral defense
• primary and secondary RNAs (amplification of the response) • cytoplasmic and nuclear Argonautes • systemic RNAi, sensitive, cheap, temperate areas worldwide
0.5 - 1.0x106 dsRNA molecules per each gonad arm Tabara et al., 1998
Nematodes
nucleus
cytoplasm
Dicer
ALG-1/2
gene control
AGO
AAAAA
inhibition of translation
AIN-1
pre-miRNA
miRNA
RNA clearance
exoRNAi
miRNA 22-23 nt
RDE-1
AAAAA
mRNA cleavage
RDE-8
RdRP
WAGOs
dsRNA
endoRNAi antiviral defense replication
injection feeding soaking
dsRNA dsRNA
DRH-1
1o siRNA
1o siRNA 22-23 nt
22G RNA
DRH-3
2o siRNA
Dicer
gene control
ERGO-1
AAAAA
mRNA cleavage
RdRP
WAGOs
RDE-4
1o siRNA
1o siRNA 26G RNA
22G RNA
DRH-3
2o siRNA
Dicer
immunity
RDE-1
AAAAA
mRNA cleavage
RdRP
SAGO-2
RDE-4
1o siRNA
22G RNA
DRH-3
2o siRNA
ERI
ERI
pri-miRNA
Microprocessor complex
RDE-8
1o siRNA 22-23 nt
DRH-1
Dicer RDE-4
Plants
AGO1
DCL2 DCL3
AGO10 AGO7
DCL1
miR-390 miR-156/166 U U A A
AGO2
MAIN miRNA PATHWAY
AGO4/6/9
21 nt 24 nt
long inverted repeats (evolving miRNAs)
ALTERNATIVE miRNA PATHWAY
DCL4
• highly complex RNA silencing system 4x Dicer, 10-20 Argonautes • a number of small RNAs, TGS & PTGS effects
miRNA pathway in plants & animals
gene control
Plants
mRNA cleavage inhibition of translation
pre-miRNA
HYL1
AGO1 miRNA 21 nt
pri-miRNA
SE
HYL1 SE DC
L1
DC
L1
AGO1
AAAAA
SUO
HEN1 HEN1
nucleus cytoplasm
nucleus cytoplasm
Arthropods
AGO1
gene control
AGO1
AAAAA
inhibition of translation
GW182
LOQS
miRNA 21-23 nt
Dicer-1
nucleus cytoplasm
Mammals
AGO1-4
gene control
AGO1-4
AAAAA
inhibition of translation
GW182
TARBP2
miRNA 21-23 nt
Dicer-1
pre-miRNA
pri-miRNA
pre-miRNA
pri-miRNA
DGCR8
DGCR8
Drosha DGCR8
DGCR8
Drosha
Plants
RDR6
RNA clearance (post-transcriptional)
transgene & viral silencing
AGO
dsRNA
viral long hairpin
21/22 nt siRNA
SDE3
sense RNA
RDR6 SGS3
DCL4/2 DCL3
AGO4/6
24 nt siRNA
RdDM AGO
SDE3
DNA methylation (transcriptional)
HEN1 HEN1 DRB3 DRB4
sense RNA
TAS loci
AGO miRNA
RDR6
DCL4
AGO1/7
tasiRNA
21nt tasiRNA
Gene regulation during development
HEN1 DRB
Plants – transcriptional silencing
Canonical RdDM Non-canonical RdDM
• highly complex RNA silencing – crosstalks & redundancy
Timeline
• extremely large volume of literature • majority not related to the review purpose (RNAi technology,
miRNA biology, innate immunity …)
Pubmed: RNAi OR RNA interference OR miRNA OR microRNA OR dsRNA
Timeline
1990 2000 2010 2015
discovery of RNAi
RNAi mechanism solved (AGO2 crystalized) co-suppression
1st miRNA Let-7
& siRNA
Dicer discovered
Dicer crystalized GW182:AGO2
Single-molecule analysis of AGO binding
pre-RNAi era - mainly plant PTGS research - initial miRNA research
RNA silencing core molecular mechanism
deciphering - mutation screens - biochemical approach
miRNA research
Plant co-suppression, PTGS, VIGS, TIGS etc. mechanisms
RNAi research
Literature review process
1. Searches in bibliographic databases n = 641 975
2. Citation pearl growing using publications known to be landmark publications in the field. (Annex C)
3. Removal of duplicates (compilation of a comprehensive set of scientific and grey literature).
4. Exclusion of references published since 2000 without DOI
5. Filtering for relevance to individual ELS questions
6. Screening of titles and abstracts
7. Study selection based on full-text reports
n = 682 911
n = 239 987
n = 190 734
1. Searches in bibliographic databases n = 641 975
2. Citation pearl growing using publications known to be landmark publications in the field. (Annex C)
3. Removal of duplicates (compilation of a comprehensive set of scientific and grey literature).
4. Exclusion of references published since 2000 without DOI
5. Filtering for relevance to individual ELS questions
6. Screening of titles and abstracts
7. Study selection based on full-text reports
n = 682 911
n = 239 987
n = 190 734
Literature review process
reference database
Scopus
keyword search
Pubmed WoS
citations of 47 landmark papers covers highly-cited pioneering papers from the pioneering times when
nomenclature was not established and uniformly adopted across the field
ProQuest
Literature review process
double strand* rna, dsrna rna interference, rnai, gene silenc*, ptgs Dicer, rnase III, argonau*, ago1, ago2, Piwi, wago, rde1 or rde-1, r2d2 tarbp2 or trbp2 mirna or microrna, sirna, 21u rna oligoadenylate, Pkr
Literature review process
1. Searches in bibliographic databases n = 641 975
2. Citation pearl growing using publications known to be landmark publications in the field. (Annex C)
3. Removal of duplicates (compilation of a comprehensive set of scientific and grey literature).
4. Exclusion of references published since 2000 without DOI
5. Filtering for relevance to individual ELS questions
6. Screening of titles and abstracts
7. Study selection based on full-text reports
n = 682 911
n = 239 987
n = 190 734
- described in detail in 2. Data & Methodologies
SPECIFIC SET-UP FOR EACH TASK/ELS QUESTION OR TAXONOMIC GROUP:
Literature review process
MAMMALS BIRDS FISH MOLLUSCS ANNELIDS ARTHROPODS NEMATODES PLANTS
choice of keywords for
reference inspection
Literature review process
references with abstracts with
highlighted relevant
keywords
relevant/irrelevant choice
chosen filtering keywords
exclude
include
filtering keywords
Literature review process
publication type annotation
optional annotation buttons
Literature review process
1. Searches in bibliographic databases n = 641 975
2. Citation pearl growing using publications known to be landmark publications in the field. (Annex C)
3. Removal of duplicates (compilation of a comprehensive set of scientific and grey literature).
4. Exclusion of references published since 2000 without DOI
5. Filtering for relevance to individual ELS questions
6. Screening of titles and abstracts
7. Study selection based on full-text reports
n = 682 911
n = 239 987
n = 190 734
- described in detail in 2. Data & Methodologies
lack of 3’ overhangs
induces IFN via Rig-I
dsRNA > 30 bp activates PKR and 2’,5’-OAS
some sequence
motifs within ssRNA
can activate IFN cationic lipid-RNA complexes
activate IFN via TLR3 and TLR7
5’ triphosphate introduced by
phage RNA polymerases
activates IFN
siRNA < 30 bp can activate PKR
lack of 3’ overhangs
induces IFN via Rig-I
dsRNA > 30 bp activates PKR and 2’,5’-OAS
some sequence
motifs within ssRNA
can activate IFN cationic lipid-RNA complexes
activate IFN via TLR3 and TLR7
5’ triphosphate introduced by
phage RNA polymerases
activates IFN
siRNA < 30 bp can activate PKR
Interferon response induced by siRNAs
24 h
ou
rs
72 h
ou
rs
mock
siRNA A
siRNA B1
siRNA B2
siRNA C
mock
siRNA A
siRNA B1
siRNA B2
siRNA C
dsRBD Zβ deaminase Zα
NLS NES ADAR1p150
ADAR1p110
ADAR2
ADAR3
Adenosine deamination
Kono & Akiyama, 2013
DOI: 10.5772/55203
nucleus
cytoplasm
ADAR1
degradation
?
AGO
Dicer Dicer AGO
dicing
RISC-loading complex
asymmetry sensing
HSP90
AGO
Dicer
HSP90
Argonaute loading passenger strand removal
Argonaute loading AGO
sense siRNA strand (passenger)
antisense siRNA = targeting (active) strand!
5’-CGUACGCGGAAUACUUCGAdTdT-3’
|||||||||||||||||||
3’-dTdTGCAUGCGCCUUAUGAAGCU-5’
• siRNA duplex undergoes loading of one of the strands on RISC • 5' portion of the selected strand is paired less stably than its 3' portion • ssRNA could reconstitute RISC; 10- to 100-fold higher concentrations required
relative to siRNA duplexes (Martinez et al., 2002, Cell. 110(5):563-74)
Acknowledgements
RIKILT Wageningen UR
Jeroen van Dijk
Martijn Staats
Marleen Voorhuijzen
Martijn Slot
Roberta Mariot
Joseph Evaristo
Rico Hagelaar
2
WUR - Biometris
Hilko van der Voet
WUR – Plant breeding
Ronald Hutten
Richard Visser
University of Nijmegen –
Chemometrics
Jeroen Jansen
SAFETY ASSESSMENT OF A NEW GM VARIETY
3
Parent crop
Identity, phenotypic &
agronomic performance
History of safe use
Compositional analysis
Donor, transgene(s) and delivery process
Description of donor
Description of vector DNA
Transgene delivery process
Characterisation of introduced
DNA
Characterisation of insertion site
Characterisation of gene
product(s)
Structure, identity and
characterisation
Mode of action/Specificity
Toxicity
Allergenicity
New GM crop
Identity, phenotypic &
agronomic performance
Nutritional analysis
Compositional analysis
Safety analysis
(animal studies)
Focus: potential presence of unintended effects of the genetic modification
Unintended effects
4
If the DNA code is not clear
If we can not interpret observed changes in the DNA
We use the compositional data
(targeted analyses)
We use the compositional data (targeted analyses
Why may potential unintended effects not be relevant?
• We have a long history of innovative plant breeding with
very few examples of adverse effects
• Plant breeders take their responsibility to develop new crop
varieties that are safe and nutritious
• It is unlikely that a safe variety is transformed into an unsafe
variety as the result of unintended effects
Unintended effects
5
If the DNA code is not clear
If we can not interpret observed changes in the DNA
We use the compositional data
(targeted analyses)
We use the compositional data (targeted analyses
Why may potential unintended effects be relevant?
• A range of new and powerful techniques (Crispr-Cas,
synthetic biology) allow the rapid introduction of new RNAs,
proteins and secondary metabolites, unknown to our food
supply chain, possibly even unknown to nature.
• Because of the targeted and precise techniques plant breeding
programmes are becoming shorter with less time
(years/harvests) to assess new varieties for altered
characteristics
Unintended effects
6
If the DNA code is not clear
If we can not interpret observed changes in the DNA
We use the compositional data
(targeted analyses)
We use the compositional data (targeted analyses
• Hazard identification on the basis of:
o Molecular characterisation
o Phenotypic analysis
o Agronomic performance
o Compositional analysis (targeted analyses)
Unintended effects
7
If the DNA code is not clear
If we can not interpret observed changes in the DNA
We use the compositional data
(targeted analyses)
We use the compositional data (targeted analyses
• Hazard identification on the basis of:
o Molecular characterisation
o Phenotypic analysis
o Agronomic performance
o Compositional analysis (targeted analyses)
o Animal feeding trials with whole foods
Unintended effects
8
If the DNA code is not clear
If we can not interpret observed changes in the DNA
We use the compositional data
(targeted analyses)
We use the compositional data (targeted analyses
• Hazard identification on the basis of:
o Molecular characterisation
o Phenotypic analysis
o Agronomic performance
o Compositional analysis (targeted analyses)
o Animal feeding trials with whole foods
In the GRACE project:
- animal feeding trials with whole foods
- detailed compositional analyses - same maize materials
Compositional analysis (targeted)
10
Non-GM counterpart
GM variety
Conventional variety 1
Conventional variety 2
Conventional variety 3
Conventional variety 6
Conventional variety 5
Conventional variety 4
Compositional analysis,
targeted vs omics analysis
11
Targeted analyses:
• key nutrients (macronutrients/micronutrients),
• key anti-nutrients, including natural toxins
Omics analyses:
• Transcriptome: all transcribed DNA products (RNA)
• Proteome: all proteins
• Metabolome: all secondary metabolites
Unintended effects
12
If the DNA code is not clear
If we can not interpret observed changes in the DNA
We use the compositional data
(targeted analyses)
We use the compositional data (targeted analyses
Targeted analyses • Few hundreds of end-
points
• Limited coverage of individual metabolic routes
• Advanced data analysis is required (comparison with conventional varieties)
• Natural variation needs to be included!
Omics analyses • Many thousands of end-
points
• Broad coverage of individual metabolic routes
• Advanced data analysis is required (comparison with conventional varieties)
• Natural variation needs to be included!
Omics analyses
13
If the DNA code is not clear
If we can not interpret observed changes in the DNA
We use the compositional data
(targeted analyses)
We use the compositional data (targeted analyses
Omics analyses lead to very large datasets. The question is: how to analyse for meaningful differences in the omics profiles, given the fact that there is much natural variation between plants due to e.g. - Genotype - Environmental conditions of growth (soil and climatological conditions) Model developed with Wageningen UR Biometris (statisticians) and University of Nijmegen, dept of Chemometrics Basic criterium: profiles of varieties that can not be considered as safe should fall outside of the one class
14
Compare transcriptomics profiles
Omics profiles of
commercial crop plants
Build a one-class
classification tool
Classify the new profile
Omics profiles of
commercial crop plants
Build a one-class
classification tool
Classify the new profile
Within the safe one-
class?
Further analysis
No further analysis
Yes No
GRACE conclusions Unintended effects can likely be more effectively traced by informative
omics analyses compared to animal feeding studies with whole foods:
GRACE data have shown that the comparative safety assessment
(Implementation Regulation 503/2013) can also be adopted for omics
data, e.g. using the one-class model approach: the GM variety can be
compared to its closest conventional comparator, as well as to a range of
conventional varieties.
GRACE data have shown that the one-class model classifies mycotoxin-
contaminated maize samples as outside of the one ‘safe’ class, the
results would provide a scientific basis for further analysis.
GRACE conclusions
• All maize varieties fed to the test animals (90-d) in the course of
GRACE were classified by the one-class model as inside of the one
‘safe’ class
• The one-class model classifies experimental potato varieties that are fit
for human consumption but genetically more distant from the lines that
are currently consumed, in almost all cases as outside of the one ‘safe’
class (indicating that the one-class model represents a conservative
approach)
GRACE conclusions
• Based on these observations: omics data provide qualitatively
structured details of the plant material which facilitates a non-targeted
“safety“ evaluation.
• Thereby it provides a better basis for the decision on the scientific
rationale to frame the subsequent risk assessment steps, which may
include the performance of an animal feeding trial with the plant-
derived whole food/feed
1
Cartagena Protocol on Biosafety and Synthetic Biology
Boet Glandorf
GMO Office, RIVM
The Netherlands
3
Objective Cartagena protocol
5
To contribute to ensuring the safe transfer, handling and use of LMOs resulting
from modern biotechnology that may have adverse effects on the biological
diversity, taking also into account risks to human
health
Cartagena Protocol
6
•Negotiated under the Convention on Biological Diversity (CBD)
• Adopted 29 January 2000 after 4 years of intense negotiations • Entry into force: 9 September 2003 • 170 ratifications/ accessions • 8 meetings of the governing body (COP-MOP)
Scope
7
Applies to: Transboundary movement, transit, handling and use of all LMOs that may have adverse effects on biodiversity, taking also into account risks to human health
How does the Protocol work?
8
The Protocol establishes rules and procedures to
regulate the movements of LMOs from one country to
another
Categories of LMOs
9
•LMOs for intentional introduction into the environment (such as seeds and live fish)
•LMOs intended for direct use as food, feed or processing, LMOs-FFP (such as agricultural commodities – corn, canola and cotton)
•LMOs for contained use (such as bacteria for laboratory scientific experiment)
Procedures for Transboundary Movements of LMOs
Two key procedures:
– The Advance Informed Agreement (AIA) procedure
– Procedures for LMOs intended for direct use as food, feed or for processing (LMOs-FFP)
Precautionary Approach
Objective: Safe Transfer, Handling and Use of
LMOs
Biosafety Clearing-House (BCH) , Capacity-Building,
Compliance and COP-MOP
Supporting Mechanisms:
• Risk
Assessment
• Risk
Management
•Information
Sharing
•Public
Awareness &
Public
Participation
• Rules/
Procedures:
- AIA Procedure
- Procedure for
FFP
• Decision -
making
•Handling,
Transport,
Packaging and
Identification:
- Documentation
for Shipment
- Standards
Key Provisions of the Protocol
12
Regulation (EC) 1946/2003 regulates transboundary movements of GMOs and transposes the Cartagena Protocol on Biosafety into EU law The Protocol sets common rules for the trans-boundary movement of Living Modified Organisms to ensure the protection of biodiversity and human health globally. The Regulation, which addresses in particular exports of GMOs, obliges EU countries to take legal, administrative and other measures to implement their commitments under the Protocol. It establishes the procedures for the trans-boundary movement of GMOs including: - notification to importing parties - information to the Biosafety Clearing House - requirements on identification and accompanying documentation
Cartagena protocol Main discussion items at last COP MOP meetings were:
• Adoption/endorsement of Guidance on Risk Assessment
of LMOs (Road map)
• Development of further RA guidance for specific groups
of LMOs, such as LM fish and organisms obtained by synbio
13
Synthetic biology: new and emerging issue under the CBD?
2012 Decision XI/II New and Emerging issues
Noting, based on the precautionary approach, the need to consider the potential positive and negative impacts of components, organisms and products resulting from synthetic biology techniques on the conservation and sustainable use of biodiversity, requests the Executive Secretary, subject to availability of resources…
● Compilation of developments in synbio
● Synthesis of information on synbio
● Review by technical body (SBSTTA)
● Is synbio a new and emerging issue?
14
Synthetic biology: new and emerging issue under the CBD
2014 Decision XII/24. New and emerging issues: synthetic biology?
● Coordinated approach synthetic biology and Cartagena Protocol
● SBSTTA not clear if synbio is new and emerging issue
● Precautionary approach: only introduction after risk assessment, risk management is in place
● Establishment of Ad Hoc Technical Working Group (AHTEG) and online forum
● Mandate: operational definition synbio, difference synbio and LMO, benefits and risks synbio, best practices for risk assessment and monitoring, framework to address impacts
After review by SBSTTA, draft decision to be discussed in COP 2016
15
Synthetic biology: new and emerging issue under the CBD
2016 Decision XIII/17 New and emerging issues: synthetic biology
• Precautionary approach: only introduction after risk assessment, risk management is in place, also applies to organisms with a gene drive
• Current applications synbio are LMO
• Risk assessment methodology LMOs is applicable to synbio
• Unclear of some organisms obtained by synbio in the future will fall under definition of LMO
• Collection of further info on experience with synbio, such as risk assessments, effects (positive, negative)
• Extension AHTEG, online forum
• Mandate: to review recent technological developments, synbio organisms that are no LMO, best practices, detection and monitoring
18
Cartagena protocol
Cancun 2016 Draft decision
• Adoption of Guidance on Risk Assessment of LMOs
• Development of further RA guidance for specific groups
of LMOs, such as for organisms obtained by synbio
2016 Decision VIII/12
• Take note of Guidance as one of the Guidances
• No extension of the AHTEG on Risk Assessment
• No development of further guidance on LM fish and synbio
• Compilation of views on:
- topics for further guidance and
- - criteria to decide when such guidance is considered necessary
19
Next step
Outcome of:
● Online forum Cartagena Protocol
● Online forum synbio
● AHTEG synbio
will be discussed in technical body (SBSTTA) in 2018
Decisions will be taken in COP MOP (Cartagena Protocol) en COP (synbio) at the end of 2018 in Egypt, based on report SBSTTA
20
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