ArticlePDF Available
Food Research International 184 (2024) 114268
Available online 22 March 2024
0963-9969/© 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).
Novel foods, old issues: Metabarcoding revealed mislabeling in insect-based
products sold by e-commerce on the EU market
Alice Giusti
1
, Gabriele Spatola
1
, Simone Mancini , Roberta Nuvoloni , Andrea Armani
*
Department of Veterinary Sciences, University of Pisa, 56124 Pisa, Italy
ARTICLE INFO
Keywords:
Edible insects
Food authentication
Next generation sequencing technologies
Food Fraud
Consumers protection
Ofcial control
ABSTRACT
Insects intended for human consumption are considered Novel Foods according to EU legislation. marketed in
form of powders, bars, snacks are increasingly available on the EU market, especially on e-commerce. The
commercial form and the way of distribution make IBPs particularly prone to mislabeling. Literature concerning
the mislabeling occurrence in IBPs is extremely scarce. In this study, 46 processed IBPs were collected on nine EU
e-commerce platforms (e-CO) to be authenticated by metabarcoding. A 200 bp region from 16S rRNA gene was
used as molecular target. Sequencing data were processed using DADA2 R package, and sequences were taxo-
nomically assigned through BLAST analysis against GenBank. Procedural blanks and positive controls were
included in the analysis, and threshold values were established to lter the nal data. The mislabeling rate (i. e.
the mismatch between the species declared on the IBP label and the species identied by metabarcoding) was
calculated. Overall, a high mislabeling rate (33.3 %) was observed, although this percentage is inuenced by the
e-CO platform and the insect species, with A. domesticus particularly involved. The use of species not listed in
authorized Novel Food (e. g. Gryllus locorojo), and/or the partial replacement of high value species with lower
value species was highlighted for the rst time in processed IBPs. The presence of insect pests was also detected.
Metabarcoding was conrmed as an effective tool for IBPs authentication. Also, outcomes from this study can
provide useful data on the main issues involving the EU IBPsmarket, that can represent an incentive to reinforce
both ofcial controls and FBOs self-controls on these poorly investigated products.
1. Introduction
The world population will reach an estimated 9.7 billion in 2050
(FAO, 2021). Consequently, the demand for protein-rich food is
growing, and the world will have to produce 70100 % more food
(McKenzie & Williams, 2015). In this context, the interest in the use of
insects as food is increasing worldwide (Van Huis, 2020). This global
attention on entomophagy is especially due to the lower environmental
impact of insects production, compared to conventional livestock
(Nadeau et al., 2015; Oonincx & De Boer, 2012; Van Huis & Oonincx,
2017). Moreover, some edible insects were proved to have signicantly
healthier Nutrient Value Score than beef and chicken (Payne et al.,
2016), which makes them valuable alternative proteins.
At the EU level, insects intended for human consumption are
considered Novel Food, meaning any food that was not used for human
consumption to a signicant degree within the Union before 15 May 1997as
provided by the Regulation EU No 2015/2283. Novel Foods must be
authorized by Commission Implementing Regulations (CIRs) that add
them to the Union List of Novel Food. Nowadays, some Food Business
Operators (FBOs) have been authorized to place dened types of insects
based-products (IBPs) on the EU market. These IBPs can be made with
yellow mealworm (Tenebrio molitor) (CIR EU 2021/882; CIR EU 2022/
169), migratory locust (Locusta migratoria) (CIR EU 2021/1975), house
cricket (Acheta domesticus) (CIR EU 2022/188; CIR EU 2023/5) and
lesser mealworm (Alphitobius diaperinus) (CIR EU 2023/58). Each CIR
also provides the commercial categories (e. g. whole frozen, dried,
powder etc.) in which IBPs can be marketed, the percentage of insect
allowed for each commercial category, and the specic labeling
requirements.
The acceptance rate of the EU consumers towards edible insects is
reported to be still low (Kornher et al., 2019). This is mainly due to the
sense of disgust for the entomophagy practice, which is far away from
the traditional behaviors of Western citizens (La Barbera et al., 2018;
Mancini et al., 2019a, Sogari et al., 2019). Thus, reducing the visibility
* Corresponding author.
E-mail address: andrea.armani@unipi.it (A. Armani).
1
These authors equally contributed to this work.
Contents lists available at ScienceDirect
Food Research International
journal homepage: www.elsevier.com/locate/foodres
https://doi.org/10.1016/j.foodres.2024.114268
Received 9 February 2024; Received in revised form 19 March 2024; Accepted 20 March 2024
Food Research International 184 (2024) 114268
2
of insects by using them as ingredients of IBPs can represent a valid
option to overcome rejection to insects consumption (Tzompa-Sosa
et al., 2023). For this reason, different kinds of processed IBPs (such as
powders, bars, snaks) are currently available and growing on the EU
market (Spatola et al., 2024; Mancini et al., 2022). These IBPs are mainly
sold online through e-commerce platforms (Spatola et al., 2024; Pippi-
nato et al., 2020).
The distance selling method (e-commerce) was reported as an
important way of distribution of not authorized Novel Food on the EU
market (DGSANTE, 2019). In addition, the whole insect key features
that lack in processed IBPs may encourage to commit illicit substitution.
Indeed, the possibility that less valuable or not-authorized species un-
declared in the label are added/mixed with the declared one in a multi-
species matrix should be considered. In addition, IBPs are sold for higher
prices with respect to other foods of the same category (Lombardi et al.,
2019; Spatola et al., 2024), further making them particularly prone to
deceptive practices, especially mislabeling. According to the EU Com-
mission, mislabeling is the false claims or distortion of the information
reported on the label (European Commission, 2018), and it is currently
the preponderant form of food fraud in the EU (Visciano & Schirone,
2021). Respect to insects sold for human consumption, mislabeling data
are still very scarce. A recent study evaluating the labeling compliance
to EU legislation of IBPs sold online identied issues respect to the in-
formation to consumers (Spatola et al., 2024). Non-compliances were
mainly related to the absence, incompleteness, or in-accuracy of the
additional specic labeling requirementsreported by CIRs, such as the
name of the foodand allergens statement(Spatola et al., 2024).
Food authentication consists of verifying that the nature and char-
acteristics of the food match with label declarations (Morin & Lees,
2018), and DNA-based techniques are the analytical tools most used for
this purpose (Giusti et al., 2023a). DNA barcoding has been especially
used for the authentication of sh/seafood and meat/poultry (Fernandes
et al., 2021; Galimberti et al., 2015; Giusti et al., 2023a; Hellberg et al.,
2017; Nehal et al., 2021). As regards insects used as food, this technique
was applied only in one study analyzing whole preserved and prepared
insects sold in UK (Siozios et al., 2020). In this study, cases of disparity
between barcode identity and package contents was actually revealed
(Siozios et al., 2020).On the contrary, DNA barcoding represents a
central component of insect species identication for environmental and
agriculture biosecurity purposes (Armstrong, 2010; Hodgetts et al.,
2016; Piper et al., 2019). Interestingly, its potential use in the identi-
cation of insect pest species in processed food was tested (Watanabe
et al., 2023). The efciency of DNA barcoding is however limited by the
number of target species that can be simultaneously identied. Outputs
generally show only one species, usually the most represented in the
sample, failing to identify the others (Giusti et al., 2024). This limitation
makes DNA barcoding not appropriate for the analysis of complex
matrices consisting of multiple species (Giusti et al., 2024; Haynes et al.,
2019).
Metabarcoding, or target amplicon sequencing, is a combination of
DNA barcoding with Next Generation Sequencing Technologies (NGS)
which could allow to overcome DNA barcoding limits, by detecting a
larger number of species in a sample simultaneously (Fernandes et al.,
2021). The high potential of this method in analyzing complex mixed
insect communities was highlighted (Piper et al., 2019). Additionally, it
was successfully applied to the authentication of insects used for human
consumption in the study of Hillinger et al. (2023), which is currently
the only available.
The aim of the present study was to authenticate processed IBPs
collected on different EU e-commerce platforms by metabarcoding, to
collect data on composition and possible mislabeling pattern for this
type of less investigated Novel Foods. Results from this study could
extend the eld of application of this technique to IBPs analysis, sup-
porting both ofcial control and companiesself-control plans.
2. Material and methods
2.1. Sampling
2.1.1. IBPs collection. A total of 46 IBPs were purchased from nine
different e-commerce platforms (e-CO1 to e-CO9), selected among those
reported in Spatola et al. (2024) as selling authorized IBPs within the EU
market. The collection was performed in the period October-November
2023 (Table 1). A convenience, non-probabilistic sampling was con-
ducted, structured to include a proportional number of IBPs per type and
brand, notwithstanding the market availability in the collection period
and the e-CO possibility to ship in Italy. The IBPs were composed of the
four insect species currently used in the authorized IBPs at the EU level,
A. domesticus, A. diaperinus, T. molitor and L. migratoria. The collected
IBPs included powders, premix, pasta, chips, cookies, bars, crackers,
sausages, etc. (details in Table 1), and they were conventionally grouped
in categories (Table 1). The IBPs composed of whole insects were not
included.
2.1.2. Reference samples. Morphologically identied specimens of the
species: A. diaperinus, A. domesticus, L. migratoria, T. molitor, Hermetia
illucens and Zophobas morio (total 12 specimens) and of honeybee (Apis
mellifera) (this last to be used as extraction positive control as described
in section 2.2.2) were provided by the Department of Veterinary Sci-
ences of the University of Pisa, Italy.
2.2. Preparation of the IBPssamples and total DNA extraction
2.2.1. Preparation of the IBPssamples. For the IBPs other than pow-
ders and premix (Table 1), half of the package content was taken and
nely ground to a powder or homogeneous paste in a steel blender with
removable blades. Grinding was carried out under a chemical fume hood
to avoid contamination between successive grindings sections (GS) due
to the persistence of traces of powdered product. The hood worktop was
also deterged and decontaminated between successive GS. The GS were
sorted into species and ordered as follows: i) GS-1 and GS-2 included 15
IPBs made of A. domesticus (n =10 and n =5, respectively, powders/
premix excluded); ii) GS-3 and GS-4 included eight IPBs made of
A. diaperinus (n =4 for each GS, powders/premix excluded); iii) GS-5
included six IBPs made of T. molitor (powders excluded). The IPB
made of L. migratoria, being a powder, was not included in the GS. To
highlight that, when IBP-8 and IBP-9 (protein bars made with insects
A. diaperinus -, chocolate, and fruit) packages were opened, specimens of
larval stages of common insect pests were found. These samples were
however analyzed after removing the pest larvae in order to not ground
them during the preparation of the samples.
Two powdered samples (duplicates) from each grinded IPB and from
the IPBs already made of powder/premix were taken for the subsequent
analysis, for a total of 92 IPBssamples (i. e. 46 IBPs in duplicates).
2.2.2. Total DNA extraction. Total DNA was extracted from the
reference samples (section 2.1.2.) and from the 92 IBPssamples (sec-
tion 2.2.1.) using NucleoSpin®Food (Macherey-Nagel GmbH & Co. KG,
Düren, Germany) following the manufacturers instructions. All DNA
extraction procedures were conducted under a chemical fume hood.
Overall, seven DNA extractions sessions (from EXT-0 to EXT-6) were
performed, each referrable to one extraction day (seven extraction
days). The reference samples were processed in EXT-0. EXT-1/EXT-2
and EXT-3/EXT-4, EXT-5 and EXT-6 included the IBPssamples obtained
from A. domesticus, A. diaperinus, L. migratoria, T. molitor, respectively.
Each total DNA extraction from EXT-1 to EXT-6 also included one
sample of A. mellifera to be used as extraction positive control and one
procedural blank, with no tissue.
2.2.3. Total DNA evaluation. The total DNA concentration and purity
were evaluated with Nanodrop ND-1000 spectrophotometer (NanoDrop
Technologies, Wilmington, DE, US) by two subsequent measurements of
the absorbance value at 260 nm and calculation of A260/A280 and of
A260/A230 ratio according to manufacturers indications. Ratios A260/
A. Giusti et al.
Food Research International 184 (2024) 114268
3
A280 and A260/A230 around 2.0 were considered as satisfactory values
of DNA purity. At the end of this phase, total DNA samples of IBPs
duplicates were pooled together, so that the IBPs samples returned to be
46.
2.3. Primer testing
The 16Sr RNA region (200 bp) was amplied from DNA samples
obtained by the reference samples using the primer pair Fwd-I-3 (5
-
TWACGCTGTTATCCCTAAGG-3
) and Rev-I-1 (5
- GACGAGAA-
GACCCTATAGA-3
) proposed by Hillinger et al. (2023). The following
PCR protocol was adopted: 15 min initial denaturation at 95 C, fol-
lowed by 35 cycles of 30 s each at 95 C, 58 C, and 72 C, and a 7 min
nal elongation at 72 C. PCR products were resolved by electrophoresis
on a 2 % agarose gel (GellyPhor LE, Euroclone SPA, Milano, Italy)
stained with GelRed Nucleid Acid Gel Stain (Biotium, Hayward, CA,
USA). The presence of PCR products of the expected length was visu-
alized by UV light transilluminator.
2.4. Metabarcoding analysis
2.4.1 Library preparation, validation, and quantication. The overhang
adapter sequence reported in the Illumina 16S Metagenomic Sequencing
Library Preparation Guide (LPG) (https://support.illumina.com/down
loads/16s_metagenomic_sequencing_library_preparation.html) were
added to the primer pair Fwd-I-3/ Rev-I-1 as follows: forward overhang
5
-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG- [Fwd-I-3] and
reverse overhang 5
GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG-
[Rev-I-1]. Overall, 62 DNA samples were amplied, including: a) 46
IBPs samples; b) six extraction positive controls; c) six procedural
blanks; d) two PCR positive controls; e) two PCR negative controls (with
no DNA). For each sample, the following PCR reaction was set: 2.5 µl of
DNA, 5 µl of primer forward overhang, 5 µl of primer reverse overhang,
12.5 µl of 2x KAPA HiFi HotStart ReadyMix (KAPA Biosystems). The
same PCR program reported in section 2.3 was used and the presence of
PCR products of the expected length was visualized by UV light trans-
illuminator. Then, the AMPure XP beads kit (Beckman Coulter S.r.l.) was
used to purify the amplicons following the manufacturers instructions.
Dual indices and Illumina sequencing adapters were attached to obtain
the nal libraries using Illumina® DNA/RNA UD Indexes Set A, Tag-
mentation, following the manufacturers instructions. The nal libraries
were further cleaned up using AMPure XP beads kit (Beckman Coulter S.
Table 1
Insect-based products (IBPs) collected in this study, with relative description and
e-commerce platform (e-CO). The categories were conventionally assigned
based on the label information.
IBP Declared
species
Label information Category e-CO
IBP-
1
A. domesticus Cricket powder Powder e-
CO2
IBP-
2
T. molitor Sfogliette Snacks e-
CO1
IBP-
3
T. molitor Vanilla cookies Bakery
products
e-
CO1
IBP-
4
T. molitor Pizza chips Snacks e-
CO1
IBP-
5
T. molitor Insect powder Powder e-
CO1
IBP-
6
A. domesticus Cricket cracker Bakery
product
e-
CO4
IBP-
7
A. domesticus Cricket cracker Bakery
product
e-
CO4
IBP-
8
A. diaperinus Protein bar with insects,
chocolate and fruit
Protein
product
e-
CO8
IBP-
9
A. diaperinus Protein bar with insects,
chocolate and fruit
Protein
product
e-
CO8
IBP-
10
A. diaperinus Protein bar with insects,
caramel and fruits
Protein
product
e-
CO8
IBP-
11
A. diaperinus Crispy bakes Bakery
product
e-
CO4
IBP-
12
A. domesticus Cricket our Powder e-
CO4
IBP-
13
A. diaperinus Dry mix of buffalo worm our,
plant protein and spices
Premix e-
CO4
IBP-
14
T. molitor Mealworm powder Powder e-
CO2
IBP-
15
A. domesticus Garlic chips Snack e-
CO2
IBP-
16
A. domesticus Chips Snack e-
CO2
IBP-
17
A. diaperinus Crisp bread Bakery
product
e-
CO5
IBP-
18
A. domesticus Chocolate squares with cricket
our and peppermint
Chocolate
product
e-
CO5
IBP-
19
A. diaperinus Chocolate squares with
buffalo worm our and peanut
butter
Chocolate
product
e-
CO5
IBP-
20
A. domesticus Oat cricket protein breakfast Protein
product
e-
CO6
IBP-
21
A. domesticus Strawberry cricket protein
blend
Protein
product
e-
CO6
IBP-
22
A. domesticus Protein bar with cricket,
chocolate and fruit
Protein
product
e-
CO6
IBP-
23
A. domesticus Protein bar with cricket,
chocolate and fruit
Protein
product
e-
CO6
IBP-
24
A. domesticus Protein bar with cricket,
chocolate and fruit
Protein
product
e-
CO6
IBP-
25
A. domesticus Protein bar with cricket,
peanut butter and cinnamon
Protein
product
e-
CO6
IBP-
26
A. domesticus Pea cricket chips Snack e-
CO6
IBP-
27
A. domesticus Pea cricket chips Snack e-
CO6
IBP-
28
A. domesticus Cricket pasta Pasta e-
CO6
IBP-
29
A. domesticus house cricket powder Powder e-
CO7
IBP-
30
A. diaperinus Buffalo worm powder Powder e-
CO7
IBP-
31
L. migratoria Grasshoppers powder Powder e-
CO7
IBP-
32
T. molitor Cracker with insect our Bakery
product
e-
CO3
IBP-
33
T. molitor Cracker with insect our Bakery
product
e-
CO3
IBP-
34
A. domesticus Chewing Spoon Bakery
product
e-
CO2
IBP-
35
A. diaperinus Buffalo sausages Meat product e-
CO9
Table 1 (continued )
IBP Declared
species
Label information Category e-CO
IBP-
36
A. diaperinus Fusilli Pasta e-
CO8
IBP-
37
A. diaperinus Fusilli Pasta e-
CO8
IBP-
38
T. molitor cacao cookies Bakery
product
e-
CO1
IBP-
39
A. diaperinus Buffalo larvae our Powder eCO9
IBP-
40
A. diaperinus Dry mix of buffalo worm our,
plant protein and spices
Premix e-
CO4
IBP-
41
A. diaperinus Dry mix of buffalo worm our,
plant protein and spices
Premix e-
CO4
IBP-
42
A. diaperinus Dry mix of buffalo worm our,
plant protein and spices
Premix e-
CO4
IBP-
43
A. diaperinus Dry mix of buffalo worm our,
plant protein and spices
Premix e-
CO4
IBP-
44
A. diaperinus Dry mix of buffalo worm our,
plant protein and spices
Premix e-
CO4
IBP-
45
A. domesticus Fusilli Pasta e-
CO4
IBP-
46
A. domesticus Fusilli Pasta e-
CO4
A. Giusti et al.
Food Research International 184 (2024) 114268
4
r.l.) before validation and quantication. For the validation, 1 µl of a
1:50 dilution of each nal library was run on an Agilent 4150 TapeS-
tation D1000 ScreenTape assay (Agilent Technologies Inc.) to verify the
size. The nal libraries were quantied using a uorometric quanti-
cation method (Qubit 4 Fluorometer, Thermo Fisher Scientic, USA).
The nal DNA concentration was calculated in nM, based on the size of
DNA amplicons as determined by Agilent 4150 TapeStation D1000
ScreenTape assay (Agilent Technologies Inc.), and applying the formula
reported in Illumina LPG. Finally, aliquots of 5 µl of diluted DNA from
each library were mixed for pooling libraries with unique indices.
2.4.2. Miseq loading and sequencing. Pooled libraries were denatured
and diluted according to Illumina LPG instructions before Miseq loading.
Pooled libraries were loaded using MiSeq Reagent Micro Kit v2 (300-
cycles), and the run included a 20 % PhiX to serve as an internal control.
2.4.3. Bioinformatic analysis. Folder containing fastq les with raw
reads were processed to generate amplicon sequence variants (ASVs)
using DADA2 R package (Callahan et al., 2016). Representative se-
quences for each ASV were taxonomically assigned through BLAST
analysis against GenBank (https://blast.Ncbi.nlm.nih.gov/Blast.cgi)
with a minimum percentage identity of 97 % and minimum query
coverage of 95 %.
2.5. Data ltering and IBPs authentication
2.5.1. Data ltering based on threshold. Threshold values were estab-
lished to lter the nal data of IBPs. In particular, for each extraction
session, the respective positive control was analysed, and the threshold
corresponded to the rst most representative percentage of sequences
found for the species (or higher taxonomic rank) other than the expected
one (A. mellifera).
2.5.2. IBPs authentication and label comparison. Once the data from
IBPs were ltered by removing species (or higher taxonomic rank) found
in percentages of the considered threshold, the IBPs nal composition
was evaluated. Outcomes of the molecular analysis were compared to
the species declared on the IBPs label to evaluate eventual mislabeling,
intended as an observed mismatch between the species declared on the
IBP label and the species detected by molecular analysis. A 95 % Con-
dence Interval (95 % CI), with alfa =5 % was calculated.
3. Results and discussion
3.1. IBPs collection
The IBPs sampling was originally planned based on the outcomes of
our previous study in which the main authorized IBPs and relative e-
commerce platforms selling within the EU market were investigated. In
that study, IBPs made with A. domesticus and T. molitor were found to be
the most sold online, followed by A. diaperinus and L. migratoria, which
had a marginal role (Spatola et al., 2024). These outcomes were also in
line with a previous survey (Pippinato et al., 2020). In the present study,
the sampling was however strongly affected by the actual IBPs market
availability at the time of collection, as well as by the inability of some e-
commerce platforms to ship in Italy. Thus, the species and/or type
representativeness of our sampling did not fully reect the previously
exposed market scenario. Indeed, only eight IBPs (17.4 %) labeled as
T. molitor were collected, even though in the study of Spatola et al.
(2024) IBPs of this species were the second most abundant online. The
majority of collected IBPs were instead labeled as A. domesticus (n =20;
43.5 %), followed by IBPs made with A. diaperinus (n =17; 36.9 %).
Finally, only one IBP (2.2 %) labeled as L. migratoria was collected. This
latter case partially reects the market scenario. Indeed, the weedy
nature and capability to be a pest for crops of L. migratoria (Scanlan
et al., 2001), together with some feeding behaviors (Van Peer et al.,
2021) of this species, may negatively inuence FBOs to rear this insect.
The sampling diversity was also observed with respect to the e-
commerce platforms. Indeed, while for e-CO4 and e-CO6 the number of
collected IBPs were 12 and 9 respectively, in the others the number was
lower, until for both e-CO5 and e-CO7 only two IBPs were collected.
Finally, according to the categories conventionally dened in this
study (Table 1), the IBPs included: nine bakery products, nine protein
products, eight powder, six premix, six snacks, ve pasta, two
chocolate productsand one meat product (Table 1). Whole insects,
although found to be the IBPs most available online (Boukid et al., 2023;
Spatola et al., 2024), were not collected in this study.
3.2. Total DNA extraction and evaluation
Total DNA was successfully extracted from all the reference samples
(including the six extraction positive controls) and the 92 IBP duplicates.
Respect to the reference samples, 1633,4 ng/µl (range 794.52984.7 ng/
µl), with ratios A260/A280 and A260/230 in the range of 2.052.24 and
1.742.45. Respect to the IBPs, an average DNA concentration of 1047.8
ng/µl (range 46.63369.8 ng/µl), with ratios A260/A280 and A260/
A230 in the range of 1.852.19 and 1.722.28, respectively. Finally, the
total DNA extracted from the six procedural blanks presented a low
average concentration (0.48 ng/µl; range 1.6 2.03 ng/µl) and low
ratios A260/A280 (1.121.50) and A260/A230 (0.361.28).
3.3. Molecular target selection and primer testing
To date, in ecological studies, the most used molecular marker for
insect species identication by both DNA barcoding and metabarcoding
is the Cytochrome c oxidase I (COI) (Elbrecht et al., 2016; Martoni et al.,
2022; Marquina et al., 2019b; Piper et al., 2019; Remmel et al., 2024).
This gene was also used to authenticate insects sold as food in UK
(Siozios et al., 2020). However, in the case of metabarcoding, the COI
low presence of high conserved nucleotide sites for design of universal
PCR primers was considered as a weakness (Deagle et al., 2014, Elbrecht
et al., 2016; Marquina et al., 2019b; Piper et al., 2019). Contrariwise, the
16S rRNA gene presents highly conserved core sequences for primer
binding and variable regions providing for taxonomic resolution (Clarke
et al., 2014; Deagle et al., 2014). Thus, this gene has been proposed and
used for insects species identication by metabarcoding, and its ef-
ciency has been by far recognized (Clarke et al., 2014, Elbrecht et al.,
2016, Marquina et al., 2019a; Piper et al., 2019). Additionally, accord-
ing to Giusti et al. (2024), 16S rRNA gene is the most used for meta-
barcoding in food of animal origin. Accordingly, also in the only one
study that authenticate insect species in processed food products by
metabarcoding (Hillinger et al., 2023), the 16S rRNA gene was selected
as target. In particular, the capability and efciency of different primer
pairs in amplifying a 200 bp fragment from 16S rRNA gene was tested in
vitro on eighteen insect species; the species selection criterion was the
afliation of these insects to the main representatives of edible insects,
and the four authorized at the EU level were included (Hillinger et al.,
2023). The nally selected primer pair (Fwd-3 and Rev-I-1) was re-
ported as applicable for the detection of insect species even in processed
or complex foods down to an insect content of only 0.1 % (Hillinger
et al., 2023). Moreover, the selected 16S rRNA region was compared in
silico for 1100 insect species, and it was observed that 92 % of these
species could be discriminated from each other (Hillingher et al., 2023).
Although we decided to use the 16S rRNA primer pair proposed by
Hillinger et al. (2023) in our analysis, we further assessed it on reference
specimens belonging to some edible insect species, testing all the four
included in authorized Novel Food. As expected, all the species were
successfully amplied.
3.4. Metabarcoding
3.4.1. Libraries validation and quantication. The 62 libraries obtained
from the samples (46 IBPs, six extraction positive controls, six proce-
dural blanks, two PCR positive controls and two PCR negative controls)
presented an average size of 377 bp (range 365390 bp). To note,
A. Giusti et al.
Food Research International 184 (2024) 114268
5
indeed, that although the 16S rRNA molecular target was actually 200
bp in length, the observed library size was inuenced by the presence of
primers, adaptors, and indexes. Libraries obtained from two out of the
six procedural blanks, as well as the library of IBP-24, presented too low
concentrations (average 1.84 ng/µl; range 0.66) to be sequenced, so that
they were discarded. All the remained libraries (n =59) presented an
average concentration of 180.3 ng/µl (range 0.66560 ng/µl) and were
therefore maintained and pooled to be uploaded on the Illumina MiSeq
sequencer.
3.4.1. ASVs generation and taxonomic assignment
Overall, 307 ASVs were generated from the fastq les of the 59
sequenced samples. Of them, 254 (82.7 %) were taxonomically assigned
to a species (n =232; 91.3 %) or to a genus (n =23; 9.1 %). By applying
the established criteria of minimum percentage identity (97 %) and
minimum query coverage (95 %), the remaining 53 ASVs (17.3 %) were
not assigned (NA).
In IBPs labeled as A. domesticus (n =19), sequences assigned to the
expected species were the most represented in 94.7 % of the cases (18
IBPs), with percentages ranging from 52.90 % to 99.25 % (Table SM-1).
Sequences assigned to A. diaperinus were instead predominant (92.31 %)
in one of these IBPs (IBP-18). Interestingly, sequences assigned to Gryllus
locorojo were also found in 78.9 % (n =15) of the IBPs labeled as
A. domesticus, and in ten of them the sequence percentages were
considerable (from 11.61 % to 44.26 %) (Table SM-1). To note that this
species has never been handled in our laboratory so that an eventual
environmental contamination during the workows can be excluded.
In IBPs, labeled as A. diaperinus (n =17), sequences assigned to the
expected species were the most represented in all the cases, with per-
centages ranging from 99.97 % to 100.00 % (Table SM-1). Interestingly,
sequences assigned to mammal species (Sus scrofa and Bos taurus) were
also found in IBP-35, although in low percentages (0.05 %). However,
since the used primer pair was specically designed for insects (Hillinger
et al., 2023), the observed percentage of mammal sequences was
probably underestimated. Indeed, the IBP-35 was included in the cate-
gory meat product, so that the presence of mammals in the ingredients
could have been not excluded, even though no indication of pork and
beef meat was reported in the ingredient list.
In the case of the unique L. migratoria IBP (IBP-31)85.06 % of the
sequences were assigned to the expected species, but a considerable
percentage of sequences (14.11 %) were also assigned to A. domesticus.
Finally, sequences of the expected species (T. molitor) were pre-
dominant in all the IBPs labeled as T. molitor (n =8), with percentages
ranging from 90.73 % to 99.96 % (Table SM-1). To note,sequences
assigned to the insect pests Plodia interpunctella and Cryptolestes pusillus
were found in IBP-8 and IBP-9, respectively, in which larval stages of
common insect pests were found and removed (section 2.2.1).. Other
than in the visible contaminated products, sequences assigned to other
insect pest species (Dermester ater, Amyelois transitella, Bruchus pisorum,
and Sitophylus oryzae) were also found in ten out of the 45 analyzed IBPs
(22.2 %). Details about the pest species found in the IBPs are reported in
Table SM-2.
Finally, A. mellifera was found to be highly predominant in all the six
extraction positive controls, with percentages ranging from 99.89 % to
100 % (Table 2). In these samples, sequences not assigned to the ex-
pected species belonged to contaminant DNA that presumably origi-
nated from cross-contamination with IBPs during the extraction. Indeed,
the contaminant species was in most cases the species declared on the
label of the IBPs of the relative extraction group (Table 2).
3.4.3. Threshold denition and data ltering. The rst thresholds
considered to lter the IBPs data according to the extraction group are
reported in Table 2, ranging from 0.00 % (EXT-2) to 0.09 % (EXT-3).
They resulted rather low, so that, with few exceptions, the IBPs taxo-
nomic patterns before and after the data ltering appeared quite similar
(Table SM-1).
The use of positive controls to establish a sequence threshold below
which a detected organism may be considered a contaminant (false
positive) is a well-recognized and recommended practice in meta-
barcoding analysis (Giusti et al., 2023b;Piper et al., 2019). A systematic
review on metabarcoding applied to the authentication of foodstuff of
animal origin reported that only 13 % of the analyzed studies included
positive controls (Giusti et al., 2024). Moreover, it was observed that
only 26.1 % of the studies ltered the data using thresholds, which were
mostly of 1 % or 2 % (Giusti et al., 2024). It should be underlined that
studies applying metabarcoding to the species identication of insects
usually reported lower thresholds to lter the data. For instance,
Elbrecht et al. (2016) reported a value of 0.003 %, while Marquina et al.
(2019a)of 0.4 %. However, since these studies analyzed environmental
samples, such permissive thresholds were needed. Indeed, environ-
mental samples typically contain hundreds of specimens of phyloge-
netically different taxa (Elbrecht et al., 2016), and all should be
detected. Contrariwise, in studies aimed at food product authentication,
the effective removal of organisms other than the product ingredients
could make it necessary to resort to higher thresholds. If the 1 %
threshold is applied to data of the present study, sequences that should
be probably interpreted as false positives are removed. Among them,
sequences of pest insect species D. ater, A. transitella, C. pusillus P.
interpunctella B. pisorum, and S. oryzae (see section 3.6) or sequences
from A. mellifera, which is the extraction positive control (Table SM-1).
Data ltered according to the 1 % threshold are reported in Fig. 1 and
Table 3, and they can be interpreted as reecting the IBPs species
composition.
Sequences assigned to the species found in IBPs and extraction pos-
itive controls were also found in the procedural blanks, but in a very low
number (few tens). We therefore considered this data unable to affect
the IBPs authentication results. Actually, despite all the precautions to
avoid environmental and cross-contaminations, a certain amount of
contaminant DNA in the procedural blanks is unavoidable, as it can
occur at any stage of the metabarcoding process, through contamination
from environmental or laboratory sources (e.g., due to aerosolization
and subsequent contamination of gloves, pipetting devices, laboratory
surfaces, etc., in addition to reagents) (Alberdi et al., 2019; Drake et al.,
2022; Jusino et al., 2019).
3.5. Label comparison and mislabeling evaluation
3.5.1. Overall. Based on data ltering by applying the selected
thresholds (section 3.4.2), 15 out of the 45 sequenced IBPs were found
mislabeled. Therefore, the overall mislabeling rate was 33.3 %, (95 % CI
32.034.6) (Table 3). To underline, however, that this percentage was
inuenced by the insect species and the e-commerce platform. Indeed,
most of the mislabeled IBPs (n =11; 73.3 % of the mislabeling cases)
Table 2
Results obtained from positive controls of each extraction group and rst
thresholds used to lter the data.
Extraction
group
sequences
(%)
Extraction group ltering
threshold (%)
EXT-1 Apis mellifera 99.97 0.02
NA 0.02
Acheta
domesticus
0.01
EXT-2 Apis mellifera 100 0
EXT-3 Apis mellifera 99.89 0.09
Alphitobius
diaperinus
0.09
EXT-4 Apis mellifera 99.95 0.05
Alphitobius
diaperinus
0.05
EXT-5 Apis mellifera 99.98 0.02
NA 0.02
EXT-6 Apis mellifera 99.98 0.02
NA 0.02
A. Giusti et al.
Food Research International 184 (2024) 114268
6
were found in IBPs labeled as A. domesticus, followed by A. diaperinus (n
=2; 13.3 %), L. migratoria (n =1; 6.7 %) and T. molitor (n =1; 6.7 %).
Mislabeling cases divided for each species are reported in the following
sections. The higher number of mislabeled IBPs was observed in e-CO4
(n =6/12; 50.0 %) and e-CO6 (n =5/8; 62.5 %), which were the most
sampled (see section 3.1). e-CO-9 has a high rate of IBPs with mis-
labeling as well, probably related to the only two IBP analyzed from this
platform. However, six e-commerce platforms out of nine (~67 %) sold
mislabeled IBPs. Further details about distribution of mislabeling cases
across species and e- commerce platforms are reported in Fig. 2 and
Table 4. As a novel and largely under-researched food product, risk
assessment into the vulnerability of insect products to adulteration is
almost non-existent (Traynor et al., 2024). According to a recent review,
no published study was found which investigated the potential fraud in
edible insect food supply chains (Traynor et al., 2024). Actually, we
found that cases of mislabeling are reported in products made of whole
insects sold for human consumption in the EU market (Siozios et al.,
2020). However, in that study, the detected mislabeling cases were not
linked to species used in currently authorized IBPs (Siozios et al., 2020).
Contrariwise, no mislabeling cases in insects sold for human consump-
tion in the EU market were detected in the other two available studies on
this topic (Hillinger et al., 2023; (Kim et al., 2019). Therefore, other than
conrming e-commerce as an important way of distribution of not
authorized Novel Food on EU market, as previously suggested by
DGSANTE (2019), our results highlighted for the rst-time mislabeling
cases in processed not whole IBPs authorized in the EU.
3.5.2 Mislabeling in IBPs labeled as A. domesticus. Mislabeling cases
were found in 57.9 % (11 out of 19) of the IBPs labeled as A. domesticus.
They were especially linked to the presence of G. locorojo or other Gryllus
spp. together with the declared species. This type of mislabeling
involved almost all the mislabeled IBPs of A. domesticus (n =10; 90.9 %).
According to the literature, G. locorojo has been considered one of the
crickets species reared to produce food and feed, together with
A. domesticus, Gryllodes sigillatus, Gryllus assimilis, and G. bimaculatus
(Ortiz et al., 2016; Govorushko, 2019). G. locorojo was rst described in
2012, both morphologically and molecularly, through the analysis of the
16S rRNA gene (Weismann et al., 2012). However, in that context, no
reference sequences were deposited on ofcial databases. Indeed, in our
study, reads/ASV were assigned to G. locorojo based on six sequences
(GenBank accession number OQ379913-19) produced in another un-
published study, which were the only available for this species. Weiss-
man et al. (2012) observed that many commercial breeders in Europe
claim to sell G. assimilis, but they were selling G. locorojo, which was
probably imported into Europe from South America in the late 1970
s or
1990
s. To note that, since epizootic A. domesticus Densovirus (AdDNV)
outbreaks devasted the U.S. cricket industry in 2009 (Pham et al., 2013;
Weismann et al., 2012), G. locorojo, presumably virus-resistant, has been
introduced as an alternative (Pham et al., 2013; Weismann et al., 2012).
Therefore, even though G. locorojo was detected as substitute species of
G. assimilis only in the pet-food industry (Weismann et al., 2012), our
results could suggest its usage also for food production. In our opinion,
two different scenarios would be possible: i) some FBOs involved into
the farming and production of cricket powder also use G. lojorojo even
though this latter one is not authorized to be placed on EU market as
food, ii) FBOs are persuaded to use G. assimilis but they are uncon-
sciously rearing and producing powder with G. lojorojo. In any case
neither G. assimilis nor G. locorojo powders are actually authorized as
Novel Food in the EU.
In the remaining mislabeled IBP of this group (IBP-18), sequences
assigned to A. diaperinus were found in very high percentage (92.31 %)
respect to those assigned to the declared A. domesticus (5.41 %). This can
be considered an evident replacement of A. domesticus with
A. diaperinus. Furthermore, IBPs of the same typology labeled as
A. domesticus and A. diaperinus, were sold at the same price on the e-
commerce platform involved (e-CO5). These facts could suggest that
during the production process a replacement of A. domesticus with
A. diaperinus may have occurred involuntarily. However, the risk of
commercial fraud must be taken into account, also considering that
powder of A. diaperinus larvae sale price was around 15,000
per ton of
product, rather than sales prices for A. domesticus range from
18,182 to
84,590 per ton of product (Niyonsaba et al., 2021).
3.5.3 Mislabeling in IBPs labeled as A. diaperinus. The only one case of
mislabeling observed for this group (IBP-35) (mislabeling rate 5.9 %)
was related to the presence of undeclared S. scrofa and B. taurus in a
product described as sausages made of insects (A. diaperinus) and
poultry. To deepen this aspect, 16S rRNA complete sequences of the
species S. scrofa, B. taurus and G. gallus (20 sequences for each species)
were retrieved on GenBank and aligned with the used primer pair (Fwd-
I-3 and Rev-I-1). As a matter of fact, in silico testing may not always
reect the real primer amplication performance. However, it can be
used to speculate primers capability in amplifying the molecular target.
As expected, also considering the high degree of conservation of 16S
rRNA gene (Armani et al., 2016) a low number of mismatching bp (one
to three) was observed in both Fwd-I-3 and Rev-I-1. This could have
allowed the amplication of S. scrofa and B. taurus from the IBPs. In the
case of poultry (G. gallus) the amplication failing could have been
Fig. 1. Sequence composition of the analyzed IBPs, after the data ltering by applying 1% threshold. Each histogram represents the percentage of sequence assigned
to different insect species for each IBP.
A. Giusti et al.
Food Research International 184 (2024) 114268
7
related to the two near mismatching bp at the 3
position of the Rev-I-1
(Armani et al., 2016).
The low rate of mislabeling found in IBPs labeled as A. diaperinus,
could be due to the fact that these IBPs were recently authorized (CIR EU
2023/58). Moreover, A. diaperinus is less expensive than other insect
species, such as A. domesticus (Niyonsaba et al., 2021). Indeed, even
though the average protein content and nutritional value of A. diaperinus
is generally considered one of the highest (Rumbos et al., 2019), this
species is also a certain pest of stored food and chicken facilities
(Rumbos et al., 2019). Moreover, it is a vector of foodborne pathogens
such as Salmonella spp. and Campylobacter spp. (Barua et al., 2023;
Rumbos et al., 2019) possibly posing a higher safety risk for consumers,
especially when good hygiene practices were not correctly applied. For
all the above-mentioned reasons, in a context of fraudulent sub-
stitutions, A. diaperinus could be thought as the substituentrather than
the substitutedspecies.
3.5.4 Mislabeling in IBPs labeled as L. migratoria. A mislabeling case
related to the presence of a considerable number of sequences assigned
to A. domesticus was observed in the unique IBP labeled as L. migratoria
(IBP-31) (mislabeling rate 100 %). In both species, the protein content is
high and technological properties are widely studied (Acosta-Estrada
et al., 2021; Clarkson et al., 2018; Mohamed, 2015;), resulting that both
L. migratoria and A. domesticus can be considered of high commercial
value. However, IBPs made with L. migratoria have higher sales price
than IBPs made with the other species, even within the same food
category (Pippinato et al., 2020). For instance, Pippinato et al (2020)
reported a price of 49.5
for 100 g of L. migratoria powder, against 12.8
for 100 g of A. domesticus powder. In addition, in a previous study
(Spatola et al., 2024) we noticed that the price of 1Kg of L. migratoria
powder varied from 378.00
to 905.30
(depending on the seller),
costing around the double of 1 Kg of A. domesticus powder sold by the
Table 3
Comparison between label declaration and metabarcoding. [a]: this IBP was not
considered mislabeled since P. interpunctella was a pest; [b]: This IBP was
considered mislabeled, since, although sequence assigned to S. scrofa e B. taurus
were found in percentage below the 1% the presence of these species was not
declared.
Declared
species
Sample Category e-CO Species ID mislabeling
A. domesticus IBP-6 Bakery
product
e-
CO4
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-7 Bakery
product
e-
CO4
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-15 Snack e-
CO2
A. domesticus NO
A. domesticus IBP-16 Snack e-
CO2
A. domesticus NO
A. domesticus IBP-26 Snack e-
CO6
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-27 Snack e-
CO6
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-28 Pasta e-
CO6
A. domesticus, G.
locorojo, G.
bimaculatus
YES
A. domesticus IBP-34 Bakery
product
e-
CO2
A. domesticus NO
A. domesticus IBP-45 Pasta e-
CO4
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-46 Pasta e-
CO4
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-1 Powder e-
CO2
A. domesticus NO
A. domesticus IBP-12 Powder e-
CO4
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-18 Chocolate
product
e-
CO5
A. diaperinus, A.
domesticus, G.
locorojo
YES
A. domesticus IBP-20 Protein
product
e-
CO6
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-21 Protein
product
e-
CO6
A. domesticus, G.
locorojo, Gryllus
sp.
YES
A. domesticus IBP-22 Protein
product
e-
CO6
A. domesticus NO
A. domesticus IBP-23 Protein
product
e-
CO6
A. domesticus NO
A. domesticus IBP-24 Protein
product
e-
CO6
NS NS
A. domesticus IBP-25 Protein
product
e-
CO6
A. domesticus NO
A. domesticus IBP-29 Powder e-
CO7
A. domesticus NO
A. diaperinus IBP-8 Protein
product
e-
CO8
A. diaperinus, P.
interpunctella
NO
[a]
A. diaperinus IBP-9 Protein
product
e-
CO8
A. diaperinus NO
A. diaperinus IBP-10 Protein
product
e-
CO8
A. diaperinus NO
A. diaperinus IBP-11 Bakery
product
e-
CO4
A. diaperinus, A.
domesticus
YES
A. diaperinus IBP-17 Bakery
product
e-
CO5
A. diaperinus NO
A. diaperinus IBP-19 Chocolate
product
e-
CO5
A. diaperinus NO
A. diaperinus IBP-30 Powder e-
CO7
A. diaperinus NO
A. diaperinus IBP-35 Meat
product
e-
CO9
A. diaperinus
(S. scrofa, B.
taurus)
YES
[b]
Table 3 (continued )
Declared
species
Sample Category e-CO Species ID mislabeling
A. diaperinus IBP-36 Pasta e-
CO8
A. diaperinus NO
A. diaperinus IBP-37 Pasta e-
CO8
A. diaperinus NO
A. diaperinus IBP-13 Premix e-
CO4
A. diaperinus NO
A. diaperinus IBP-39 Powder eCO9 A. diaperinus NO
A. diaperinus IBP-40 Premix e-
CO4
A. diaperinus NO
A. diaperinus IBP-41 Premix e-
CO4
A. diaperinus NO
A. diaperinus IBP-42 Premix e-
CO4
A. diaperinus NO
A. diaperinus IBP-43 Premix e-
CO4
A. diaperinus NO
A. diaperinus IBP-44 Premix e-
CO4
A. diaperinus NO
L. migratoria IBP-31 Powder e-
CO7
L. migratoria, A.
domesticus
YES
T. molitor IBP-2 Snacks e-
CO1
T. molitor NO
T. molitor IBP-3 Cookies e-
CO1
T. molitor NO
T. molitor IBP-4 Snacks e-
CO1
T. molitor, A.
diaperinus, L.
migratoria
YES
T. molitor IBP-5 Powder e-
CO1
T. molitor NO
T. molitor IBP-14 Powder e-
CO2
T. molitor NO
T. molitor IBP-32 Bakery
product
e-
CO3
T. molitor NO
T. molitor IBP-33 Bakery
product
e-
CO3
T. molitor NO
T. molitor IBP-38 Bakery
product
e-
CO1
T. molitor NO
A. Giusti et al.
Food Research International 184 (2024) 114268
8
same e-commerce platform. For all these reasons, a voluntary partial
replacement of L. migratoria with A. domesticus was hypothesized in our
previous study, being economically protable. However, more data are
required for IBPs of this species.
3.5.5 Mislabeling in IBPs labeled as T. molitor: Only one IBP (IBP-4)
(mislabeling rate 12.5 %) was found mislabeled for the co-presence of
A. diaperinus and L. migratoria (Table 1). It is difcult to see any eco-
nomic advantage in replacing T. molitor with L. migratoria, being the
price of L. migratoria from 2.9 to 4 times higher than the price of
T. molitor, according to Pippinato et al (2020) and Spatola et al. (2024),
respectively. Instead, regarding A. diaperinus, fraudulent partially sub-
stitution could be a valuable hypothesis. Indeed, A. diaperinus powder is
averagely cheaper than T. molitor powder (Pippinato et al., 2020) and
different studies suggest that their nutritional composition are quite
similar (Van Broekhoven et al., 2015). However, A. diaperinus, being a
pest (Rumbos et al., 2019), has a faster reproductive cycle than T. molitor
(Kureˇ
cka et al., 2021), which contributes to the reduction in production
costs in terms of yield per mass (Herdeiro et al., 2024). Additionally,
even though separate production lines have been set up in Netherlands,
previously, to facilitate the production for human consumption,
T. molitor and A. diaperinus were commonly reared on the same mixed-
grain substrate (Van Broekhoven et al., 2015). Therefore, the presence
of A. diaperinus could depend on this production strategy.
4. Conclusions
Metabarcoding was proved effective in authenticating different
kinds of IBPs. The used 200 bp 16S rRNA target region allowed to
identify at the species level almost all the obtained sequences. For the
rst time, mislabeling rate was assessed in processed IBPs authorized to
be sold in the EU market. An overall mislabeling rate of 33.3 % (was
observed, although this percentage was inuenced by the e-commerce
platform and the species considered.. Given the type of mislabeling
cases, i. e. the use of insect species not authorized in the EU and/or the
partial replacement of high value species with lower value species, the
possibility of facing voluntary deceptive practices cannot be excluded.
These ndings can enlarge the still limited knowledge on the fraud
occurrence in these products. Indeed, being IBPs considered Novel
Foods and therefore still occupying a limited market share, they are
probably less investigated with respect to other foods and, consequently,
mislabeled IBPs may more easily enter the market. This study conrms
e-commerce as particularly vulnerable to fraudulent activities. Howev-
er, more data is needed to better depict the scenario. Finally, the method
validation is crucial to be used as support for ofcial controls and FBOs
self-controls. Indeed, an increased efciency and effectiveness of con-
trols in this products may contribute to boost EU citizenscondence in
consuming edible insects.
CRediT authorship contribution statement
Alice Giusti: Writing review & editing, Writing original draft,
Methodology, Investigation, Formal analysis, Conceptualization.
Gabriele Spatola: Writing original draft, Investigation, Formal anal-
ysis, Data curation. Simone Mancini: Writing review & editing,
Formal analysis. Roberta Nuvoloni: Investigation. Andrea Armani:
Writing review & editing, Project administration, Funding acquisition,
Conceptualization.
Declaration of competing interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
Fig. 2. Mislabeled IBPs according to the labeled species and the e-commerce platform (e-CO).
Table 4
Mislabeled IBPs with relative distribution respect to the declared species and the e-commerce platform (e-CO).
e-CO Declared species Mislabeledfor e-CO
(%)
A. domesticus T. molitor A. diaperinus L. migratoria
mislabeled n. IBPs mislabeled n. IBPs mislabeled n. IBPs mislabeled n. IBPs
e-CO1 0 0 1 5 0 0 0 0 20.0
e-CO2 0 4 0 1 0 0 0 0 0.0
e-CO3 0 0 0 2 0 0 0 0 0.0
e-CO4 5 5 0 0 1 7 0 0 50.0
e-CO5 1 1 0 0 0 2 0 0 33.3
e-CO6 5 8 0 0 0 0 0 0 62.5
e-CO7 0 1 0 0 0 1 1 1 33.3
e-CO8 0 0 0 0 0 5 0 0 0.0
e-CO9 0 0 0 0 1 2 0 0 50.0
TOT 11 19 1 8 1 17 1 1 33.3
A. Giusti et al.
Food Research International 184 (2024) 114268
9
the work reported in this paper.
Data availability
Data will be made available on request.
Acknowledgements
This work is supported by the University of Pisa under the PRA
Progetti di Ricerca di Ateneo(Institutional Research Grants) - Project
no.13 PRA_2022-2023_Next Generation Sequencing per la valutazione
del rischio in food e feed a base di insetti (NGS-Ins). Progetto Eccellenza
Open Science in Co-Creative Animal ResearchOSCAR.
Authors wish to thank Prof. Antonio Felicioli for providing Apis
mellifera specimens and Prof. Maurizio Mazzei for his support in data
analysis.
Appendix A. Supplementary material
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.foodres.2024.114268.
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... In two studies previously performed by our research team, metabarcoding was applied to the authentication of seafood products (fish burgers-FBs) [5] and novel foods (insectbased products-IBPs) [28], respectively. In both studies, sequencing data obtained from 16s rRNA metabarcoding on Illumina platforms were analyzed with the open-access DADA2 R package [10] that, according to BP classification, can be considered as an example of a customizable, ASV-based CLI BP. ...
... In both studies, sequencing data obtained from 16s rRNA metabarcoding on Illumina platforms were analyzed with the open-access DADA2 R package [10] that, according to BP classification, can be considered as an example of a customizable, ASV-based CLI BP. In both these studies species substitution were detected [5,28]. ...
... Sequencing data from 24 FB samples (belonging to nine products) and 45 IBPs samples obtained from two previous studies (study 1 and study 2) [5,28] were used. The FB and IBPs samples were sequenced using Illumina NovaSeq and Miseq instruments, respectively, with a 150-bp paired-end model [5,28]. ...
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Next Generation Sequencing Technologies (NGS), particularly metabarcoding, are valuable tools for authenticating foodstuffs and detecting eventual fraudulent practices such as species substitution. This technique, mostly used for the analysis of prokaryotes in several environments (including food), is in fact increasingly applied to identify eukaryotes (e.g., fish, mammals, avian, etc.) in multispecies food products. Besides the “wet-lab” procedures (e.g., DNA extraction, PCR, amplicon purification, etc.), the metabarcoding workflow includes a final “dry-lab” phase in which sequencing data are analyzed using a bioinformatic pipeline (BP). BPs play a crucial role in the accuracy, reliability, and interpretability of the metabarcoding results. Choosing the most suitable BP for the analysis of metabarcoding data could be challenging because it might require greater informatics skills than those needed in standard molecular analysis. To date, studies comparing BPs for metabarcoding data analysis in foodstuff authentication are scarce. In this study, we compared the data obtained from two previous studies in which fish burgers and insect-based products were authenticated using a customizable, ASV-based, and command-line interface BP (BP1) by analyzing the same data with a customizable but OTU-based and graphical user interface BP (BP2). The final sample compositions were compared statistically. No significant difference in sample compositions was highlighted by applying BP1 and BP2. However, BP1 was considered as more user-friendly than BP2 with respect to data analysis streamlining, cost of analysis, and computational time consumption. This study can provide useful information for researchers approaching the bioinformatic analysis of metabarcoding data for the first time. In the field of food authentication, an effective and efficient use of BPs could be especially useful in the context of official controls performed by the Competent Authorities and companies’ self-control in order to detect species substitution and counterfeit frauds.
... Another theory would be a lack of hybridization with the other Gryllus species (Weissman et al., 2012). A recent study showed samples of A. domesticus food samples that contained considerable amounts of G. locorojo either to cross contamination during insect farming or intended use of G. locorojo to substitute A. domesticus (Giusti et al., 2024). Following authentication, the COI region was selected for primer design, and consequently sequenced in ten G. locorojo crickets as well as two G. assimilis specimens. ...
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A real-time polymerase chain reaction (PCR)-based protocol (Gloco-PCR) was validated to specifically detect Gryllus locorojo , a Gryllus species on the European market often mistaken for Gryllus assimilis . Whereas the latter species is allowed in the EU for feeding farmed animals, G. locorojo is only permitted for pets according to the current legislation. The method was developed on the basis of the cytochrome oxidase I gene, (COI), which was sequenced with thoroughly characterised G. locorojo and G. assimilis samples. The method is highly sensitive, detecting 0.8 pg G. locorojo -DNA or 0.1% G. locorojo incurred in feed, respectively. Authentic G. assimilis specimens were used to ensure that the G. locorojo method (Gloco-PCR) discriminates this closely related sister taxon, with a comfortable Ct-difference of 10-15. For cross analysis of true G. assimilis , similar primers with another probe were employed (Gassim-PCR) and the annealing temperature was increased from 60 °C to 62 °C. Under these conditions, authentic G. assimilis crickets were detectable with Ct-values around 20, while G. locorojo samples showed a low detection at cycles around Ct 35. An investigation of ten ‘ G. assimilis ’ samples collected from Germany and four other European countries revealed that all of them were of the G. locorojo type. This proves the usefulness of our approach and supports the assumption that many G. assimilis crickets marketed in the EU indeed belong to the species G. locorojo . Consequently, European legislation, currently based on a white list of allowed insect species, is critically questioned.
... A total of 42 DNA samples obtained from different types of IBPs purchased online and already authenticated by metabarcoding in a previous study (Giusti et al., 2024), were here analysed by 16S metabarcoding, in order to characterize their microbiome. ...
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The 16S rRNA metabarcoding, based on Next-Generation Sequencing (NGS), is used to assess microbial biodiversity in various matrices, including food. The process involves a "dry-lab" phase where NGS data are processed through bioinformatic pipelines, which finally rely on taxonomic unit assignment against reference databases to assign them at order, genus, and species levels. Today, several public genomic reference databases are available for the taxonomic assignment of the 16S rRNA sequences. In this study, 42 insect-based food products were chosen as food models to find out how reference database choice could affect the microbiome results in food matrices. At the same time, this study aims to evaluate the most suitable reference database to assess the microbial composition of these still poorly investigated products. The V3-V4 region was sequenced by Illumina technology, and the R package “DADA2” used for the bioinformatic analysis. After a bibliographic search, three public databases (SILVA, RDP, NCBI RefSeq) were compared based on amplicon sequence variant (ASV) assignment percentages at different taxonomic levels and diversity indices. SILVA assigned a significantly higher percentage of ASVs to the family and genus levels compared to RefSeq and RDP. However, no significant differences were noted in microbial composition between the databases according to α and β diversity results. A total of 121 genera were identified, with 56.2% detected by all three databases, though some taxa were identified only by one or two. The study highlights the importance of using updated reference databases for accurate microbiome characterization, contributing to the optimization of metabarcoding data analysis in food microbiota studies, including novel foods.
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