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Citation: Morais, S.; Toscano, C.;
Simões, H.; Carpinteiro, D.; Viegas, C.;
Veríssimo, C.; Sabino, R. Comparison
of Multi-locus Genotypes Detected in
Aspergillus fumigatus Isolated from
COVID Associated Pulmonary
Aspergillosis (CAPA) and from Other
Clinical and Environmental Sources.
J. Fungi 2023,9, 298. https://
doi.org/10.3390/jof9030298
Academic Editor: Shawn R. Lockhart
Received: 20 December 2022
Revised: 27 January 2023
Accepted: 21 February 2023
Published: 24 February 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Fungi
Journal of
Article
Comparison of Multi-locus Genotypes Detected in Aspergillus
fumigatus Isolated from COVID Associated Pulmonary
Aspergillosis (CAPA) and from Other Clinical and
Environmental Sources
Susana Morais 1,2, Cristina Toscano 3, Helena Simões 2, Dina Carpinteiro 4, Carla Viegas 5,6,7 ,
Cristina Veríssimo 2and Raquel Sabino 2,8 ,*
1Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
2Reference Unit for Parasitic and Fungal Infections, Department of Infectious Diseases,
National Institute of Health, Av. Padre Cruz, 1649-016 Lisbon, Portugal
3Microbiology Laboratory, Centro Hospitalar Lisboa Ocidental, Hospital Egas Moniz,
1349-019 Lisboa, Portugal
4Technology and Innovation Unit, Department of Human Genetics, National Institute of Health,
1649-016 Lisbon, Portugal
5H&TRC-Health & Technology Research Center, ESTeSL-Escola Superior de Tecnologia da Saúde,
Instituto Politécnico de Lisboa, 1990-096 Lisbon, Portugal
6Public Health Research Centre, NOVA National School of Public Health, Universidade NOVA de Lisboa,
1600-560 Lisbon, Portugal
7NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research
Center (CHRC), 1600-560 Lisbon, Portugal
8Instituto de Saúde Ambiental, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal
*Correspondence: raquel.sabino@insa.min-saude.pt; Tel.: +351-217519247
Abstract:
Background: Aspergillus fumigatus is a saprophytic fungus, ubiquitous in the environment
and responsible for causing infections, some of them severe invasive infections. The high morbidity
and mortality, together with the increasing burden of triazole-resistant isolates and the emergence of
new risk groups, namely COVID-19 patients, have raised a crescent awareness of the need to better
comprehend the dynamics of this fungus. The understanding of the epidemiology of this fungus,
especially of CAPA isolates, allows a better understanding of the interactions of the fungus in the
environment and the human body. Methods: In the present study, the M3 markers of the STRAf
assay were used as a robust typing technique to understand the connection between CAPA isolates
and isolates from different sources (environmental and clinical-human and animal). Results: Of
100 viable isolates that were analyzed, 85 genotypes were found, 77 of which were unique. Some
isolates from different sources presented the same genotype. Microsatellite genotypes obtained from
A. fumigatus
isolates from COVID+ patients were all unique, not being found in any other isolates of
the present study or even in other isolates deposited in a worldwide database; these same isolates
were heterogeneously distributed among the other isolates. Conclusions: Isolates from CAPA patients
revealed high heterogeneity of multi-locus genotypes. A genotype more commonly associated with
COVID-19 infections does not appear to exist.
Keywords: Aspergillus fumigatus; CAPA; STRAf assay; microsatellite; genotyping
1. Introduction
Aspergillus fumigatus is an environmental saprophyte fungus with a ubiquitous dis-
tribution in the environment (air, water, soils) and organic matter [
1
]. This species has
an increasing relevance in animal and especially in human health, causing a wide spec-
trum of diseases [
2
], and having a relatively high morbidity and mortality [
3
]. Recently,
the World Health Organization (WHO) released the WHO fungal priority pathogens list
J. Fungi 2023,9, 298. https://doi.org/10.3390/jof9030298 https://www.mdpi.com/journal/jof
J. Fungi 2023,9, 298 2 of 14
(FPPL), the first-ever list of health-threatening fungi [
4
], and A. fumigatus was included
in the critical priority group of fungi due to the impact on health and the problem of
resistance emergence.
Aspergillus fumigatus conidia are able to enter the respiratory tract of both humans and
animals, and in cases of host susceptibility, this species is capable of infecting the lower
respiratory tract and causing chronic, allergic, or invasive disease [
5
–
7
]. Clinical risk factors
usually associated with the occurrence of disease include immunosuppression, frequently
associated with neutropenia in hematological and transplant patients for example, im-
munosuppressive treatments, and some other comorbidities [
8
]. In immunocompetent
individuals, conidial inhalation usually leads simply to colonization (followed by removal
through mechanical and immunological defenses), and in the majority of cases, there is no
respiratory tract infection. However, when infected, immunocompetent individuals often
present chronic or allergic forms of the disease, since their immune system is able to prevent
an invasive infection [
2
,
9
]. Nevertheless, there are also cases of immunocompetent patients
who develop invasive infections, especially when exposed to a high burden of conidia,
mainly in workplaces where high amounts of organic matter are manipulated, representing
an occupational hazard [
10
,
11
]. Some other patient groups appear to be associated with
infections triggered by Aspergillus, namely ICU patients, especially those who require
intubation [12], patients with influenza [13], and COVID-19 positive patients [14,15].
COVID-19 associated pulmonary aspergillosis rises as a new worrying entity, par-
ticularly relevant in this global COVID-19 pandemic. COVID-19 associated pulmonary
aspergillosis patients do not exhibit the usual risk factors associated with aspergillosis,
and, therefore, CAPA diagnosis poses new challenges [
16
]. Some guidelines have been
published in order to establish standard criteria for CAPA diagnosis and treatment [17].
Due to the lack of understanding about COVID-19 at the beginning of the pandemic
and the need to assure medical personnel safety, bronchoscopy was rarely performed in
COVID positive patients [
18
]. Hence, few specimens of Aspergillus were recovered to allow
for diagnosis of aspergillosis. To overcome this problem, some other respiratory samples
such as tracheal aspirates, sputum, and bronchial secretions were therefore used for CAPA
diagnosis [19,20].
It is still not well understood why viral infections, such as SARS-CoV-2 infections,
pose a risk factor for Aspergillus infections. It is possible that when the viral infection occurs,
there is an exacerbated inflammatory response by the host’s immune system, which leads
to severe acute respiratory distress syndrome (ARDS). ARDS causes pulmonary damage,
possibly responsible for the high risk of the development of secondary infections, including
fungal infections. Adding to that, the use of some drugs for COVID-19 treatment, like
corticosteroids, may also increase the susceptibility to secondary infections [
21
–
23
]. Taking
this into account, there are no typical risk factors associated with CAPA, and there are
several cases of CAPA in immunocompetent patients, without any prior comorbidity, that
end up being fatal [
24
,
25
]. Adding up to the challenge that the disease represents, there is a
rising problem with the emergence of triazole-resistant isolates, especially those with the
TR34/L98H mutation on the cyp51A gene [
15
,
16
]. Isolates harboring this mutation show
high resistance to several triazoles, which makes treatment of infections caused by these
resistant strains even more difficult and results in poorer outcomes [17].
The high incidence of CAPA in some countries, its associated mortality [
26
,
27
], as well
as the limitations in diagnosis, highlight the relevance of epidemiological studies on this
issue, in order to reach a better understanding of fungal dynamics.
Genotyping is a very efficient approach to better understand the molecular epidemiol-
ogy of A. fumigatus because it allows the distinction among different strains of a species.
The STRAf (Short tandem repeats of Aspergillus fumigatus) assay allows the amplification
of polymorphic loci within the fungal genome in a multiplex reaction and allows for the
determination of the number of repeats for each locus. It is a very robust, reproducible
J. Fungi 2023,9, 298 3 of 14
method [
28
,
29
]. It is useful to better understand outbreaks, to have a better perception of
geographical or timely strain distribution, and to determine if there are genotypes more
frequently associated with infection. Hence, this microsatellite-based typing method using
three loci composed of tandemly repetitive stretches of three nucleotides was applied to
genotype A. fumigatus sensu stricto isolates. Our aim is to study A. fumigatus isolates from
CAPA patients and to compare them with isolates from different origins by application
of these microsatellite markers to understand how our isolates are related to A. fumigatus
isolates from different sources and geographical distributions. Our goal is to distinguish
epidemiologically related isolates, identify prevalent strains and genotypes associated with
this disease, compare environmental and clinical isolates, and determine possible routes of
acquisition of a strain or to identify possible reservoirs.
2. Materials and Methods
2.1. Selection of Aspergillus Isolates
Eleven Aspergillus fumigatus isolates obtained from respiratory samples of 10 patients
diagnosed with COVID-19 were selected for this study (characterized in Table 1). In parallel,
95 more A. fumigatus isolates were added to the study for comparison (45 environmental,
38 from respiratory samples from non-COVID+ patients and 6 from deep-seated infections
also of non-COVID+ patients, and 6 from clinical animal sources (isolates characterized in
Supplementary Table S1). These isolates were randomly selected from a database of more
than 400 Aspergillus isolates available at the Mycology National Reference Laboratory. The
isolates were cultured onto malt extract agar medium supplemented with chloramphenicol,
and DNA was extracted from a saline solution of spores, using the High Pure PCR Tem-
plate Preparation kit (Roche Diagnostics Corp., Indianapolis, IN, USA) according to the
manufacturer’s instructions.
2.2. Molecular Identification of Isolates
To identify the selected isolates at the species level, partial sequencing of the calmod-
ulin gene was carried out. Briefly, a polymerase chain reaction (PCR) was performed
in a 25
µ
L volume using Cytiva PureTaq Read-to-Go beads (Life Sciences IP Holdings
Corporation Washington, DC, USA) with 0.7
µ
M of the cmd5 (5
0
-CCG-AGT-ACA-AGG-
AGG-CCT-TC-3
0
) and cmd6 (5
0
-CCG-ATA-GAG-GTC-ATA-ACG-TGG-3
0
) primers [
30
]. The
PCR was carried out in a thermocycler under the following conditions: an initial denatura-
tion step of 95
◦
C for 10 min followed by 38 cycles at 95
◦
C for 30 s, 55
◦
C for 30 s, and 72
◦
C
for 1 min. A final extension was performed at 72
◦
C for 1 min. PCR products were analyzed
by 2% agarose gel electrophoresis and purified using the IlustraTM ExoStar enzyme system
(GE Healthcare, Chicago, IL, USA).
Sequencing of the forward chain of the gene was performed using the BigDye termi-
nator sequencing kit with the cmd5 primer. The conditions of this PCR were as follows: an
initial denaturation at 96
◦
C for 10 s, 30 cycles at 96
◦
C for 30 s, 50
◦
C for 5 s, and 60
◦
C for
4 min, followed by a final extension at 72 ◦C for 7 min.
The samples were then subjected to Sanger sequencing in the 3500 Genetic Analyzer
(Applied Biosystems
TM
, Waltham, MA, USA). The obtained sequences were edited in
Chromas 2.6.6 software (Technelysium Pty Ltd., South Brisbane, Australia), and species
identification was obtained by comparison with the sequences deposited in the BLAST
platform [
31
]. A minimum homology of 98% was the requirement to consider an acceptable
identification to species level.
J. Fungi 2023,9, 298 4 of 14
Table 1. Characterization of the isolates collected from COVID-19 patients.
Isolate Identification VA 379 VA 380 VA381 VA 382 VA 388 VA 390
VA 394 VA 392 VA399 VA 429 VA 443
Date of isolation 10 December 2020 10 December 2020 12 November
2020 9 November 2020 16 December 2021
20 January
2021
22 January 2021
14 December 2020 8 March 2021 25 July 2021 28 August 2021
Demographics
Gender Male Male Male Male Female Male Female Male Male Male
Age (y) 66 78 49 81 74 69 97 64 72 34
Underlying conditions
Diseases
COPD (steroids)
hypertension,
hypothyroidism,
ex-smoker (for
>10 y)
COPD (steroids),
Alzheimer’s
disease,
osteoporosis,
ex-smoker (for
17 y; previously >
40 PY)
None
Smoker Hypertension,
COPD (steroids),
obesity, hypertension,
dyslipidemia, Hypertension INA
Hypertension,
None
COPD Hipotiroidism insulin-dependent
diabetes,
Diabetes mellitus,
Obesity,
Cardiac
insufficiency
Diabetes mellitus,
Obesity
1st degree AV block,
psoriasis, Dislipidemia,
Acute renal lesion
vitiligo, previous
hepatitis B,
ex-smoker (for > 35 y)
Colon
adenocarcinoma
Pancitopeniae
ARDS
Mechanical
ventilation Yes Yes Yes Yes Yes Yes No No Yes Yes
Microbiology
Fungal culture
TA: TA: BALF: TA: TA: TA: TA: BALF: TA: TA:
Aspergillus section
Fumigati
Aspergillus section
Fumigati
Aspergillus section
Fumigati
Aspergillus section
Fumigati
Aspergillus section
Fumigati
Aspergillus section
Fumigati
Aspergillus section
Fumigati
Aspergillus
section Fumigati
Aspergillus section
Fumigati
Aspergillus section
Fumigati
Molecular
identification
Aspergillus
fumigatus sensu
stricto
Aspergillus
fumigatus sensu
stricto
Aspergillus
fumigatus sensu
stricto
Aspergillus
fumigatus sensu
stricto
Aspergillus
fumigatus sensu
stricto
Aspergillus fumigatus
sensu stricto
Aspergillus
fumigatus sensu
stricto
Aspergillus
fumigatus sensu
stricto
Aspergillus
fumigatus sensu
stricto
Aspergillus
fumigatus sensu
stricto
BALF GM (≥1) Not available Not available Negative Not available Not available Not available Not available Positive Not available Not available
Serum GM (≥0.5) Not available Negative Not available Not available Not available Not available Not available Not performed Not available Not available
Classification
AspICU (modified)
Algorithm Colonization Colonization Putative Putative Putative Colonization Colonization Putative Putative Colonization
ECMM/ISHAM
CAPA Criteria Possible Possible Probable Probable Probable Possible Possible Possible Probable Possible
Therapy for
Aspergillus
Antifungal Voriconazole Voriconazole Voriconazole Voriconazole Voriconazole Voriconazole None INA Voriconazole None
Legend: ARDS = acute respiratory distress syndrome; BALF = bronchoalveolar lavage fluid; BW = body weight; COPD = chronic obstructive pulmonary disease; TA = tracheal aspirate;
INA = information not available.
J. Fungi 2023,9, 298 5 of 14
2.3. Microsatellite Genotyping
The A. fumigatus sensu stricto isolates characterized in Supplementary Table S1 were
subjected to genotyping using the STRAf assay previously described by de Valk et al. [
32
],
with a high discriminatory power (0.9994). Given the high discriminatory power of each
of the three multiplex reactions of the STRAf assay [
32
] only the M3 markers, a panel
of trinucleotide markers, were used in this study. Briefly, three sets of primers were
used to amplify the three selected loci–STRAf 3A labeled with FAM (carboxyfluorescein),
STRAf 3B labeled with HEX (hexaclorocarboxyfluorescein), and STRAf 3C labeled with
NED (Table 2).
PCR conditions were previously described [
32
]. Following amplification, PCR prod-
ucts were subjected to fragment analysis. Briefly, each PCR product was diluted in distilled
water (1:30), and 1
µ
L of the diluted samples was then combined with the GeneScan
™
500 ROX
™
marker (Applied Biosystems
™
,Waltham, MA, USA). The mixture was subjected
to thermal denaturation (3 min at 95
◦
C followed by a quick cooling to 4
◦
C). The treated
samples were subjected to capillary electrophoresis in the 3500 Genetic Analyzer (Applied
BiosystemsTM Waltham, MA, USA).
Table 2.
Primers’ sequences, fluorophores used, and respective repeat units amplified (based on [
32
]).
Primer Sequence (50→30) Repeat Unit
STRAf 3A F: FAM-GCTTCGTAGAGCGGAATCAC TCT
R: GTACCGCTGCAAAGGACAGT
STRAf 3B F: HEX-CAACTTGGTGTCAGCGAAGA AAG
R: GAGGTACCACAACACAGCACA
STRAf 3C F: NED-GGTTACATGGCTTGGAGCAT TAG
R: GTACACAAAGGGTGGGATGG
Legend: F–forward; R–reverse.
The strain CD10 was used in every performed instance of capillary electrophoresis, as
positive and reproducibility control. A sample with water in the place of DNA was used in
every run as a negative control.
2.4. Fragment Analysis and Genetic Relationships
The fragments corresponding to the amplification of each locus were analyzed in the
GeneMapper
™
Software 6 (Applied Biosystems
TM
, Waltham, MA, USA) to determine their
size in base pairs (bp). This length was further converted into the number of repeats, using
calculations and reference strains.
The alleles obtained for each isolate were then analyzed in the Bionumerics 6.6 software
(Applied Maths, bioMérieux SA, Marcy-l’Étoile, France) using a categorical similarity
coefficient and an unweighted paired group method with arithmetic mean (UPGMA) for
the cluster analysis. The minimum spanning tree (MST) and dendrogram were obtained
using this software.
2.5. Genetic Relations with AfumID Isolates
The number of repeats for each allele from every isolate was included in the Afu-
mID database (https://afumid.shinyapps.io/afumID/ (accessed on 21 June 2022), and
compared with the 4049 isolates from the database [33].
3. Results
3.1. Allele Characterization
After being submitted to the species identification as described in point 2.2 of the
material and methods section, DNA of the selected A. fumigatus sensu stricto isolates
(
N = 106
) was used for the genotyping assay. The electropherograms obtained for each
isolate were analyzed, and the fragment size was determined for the three loci. The number
of repeats of each isolate was calculated, according to what is described in point 2.4. Overall,
J. Fungi 2023,9, 298 6 of 14
microsatellite multi-locus genotypes of 100 viable isolates were considered. The analysis
of these 100 isolates showed that all the microsatellite loci were polymorphic, presenting
between 17 and 37 alleles. The size ranges of the alleles as well as the corresponding
number of repeats are shown in Table 3. From the three loci analyzed, STRAf 3A had the
highest number of different alleles, and also the widest range of allele sizes. On the other
hand, STRAf 3B had the smallest range and the lowest number of different alleles.
From the referred 100 isolates, 85 different multi-locus genotypes were obtained. Of
them, 90.6% (77 out of 85) were unique and only 9.4% (8 out of 85) represented genotypes
that appeared more than once.
Table 3.
Characterization of the alleles obtained in the microsatellite genotyping study of 100 viable
Aspergillus fumigatus sensu stricto isolates.
Microsatellite Number
of Alleles
Lower Size
Allele (bp)
Higher Size
Allele (bp)
Number of Microsatellite Repeats
(Range)
Most Common Allele
(Number of Isolates)
STRAf 3A 37 129.5 283.22 7–57 25 (9)
STRAf 3B 17 159.27 273.27 9–47 11 (29)
STRAf 3C 31 73.89 207.84 4–47 20 (14)
Legend: bp–base pairs.
3.2. Genetic Relationships
The minimum spanning tree (MST) of the studied isolates shows that there is not
an obvious grouping of isolates by source and that the isolates with the same genotype
are mostly from environmental sources (the bigger light green circles) (Figure 1). Isolates
with known resistance to triazoles (any source), were highlighted using a different color
(pink), in order to understand if there was any clustering of the resistant isolates, which
was not observed (Figure 1). In the MST, there is no clustering of the isolates obtained
from COVID-19+ patients (red circles), and they are heterogeneously spread across the tree.
None of the genotypes of A. fumigatus isolates collected from COVID+ patients is common
to more than one isolate; they were all unique (Figure 1).
A dendrogram was also constructed (Supplementary Figure S1), and the most relevant
sections with the closest genetically related isolates are highlighted in Table 3. All the other
studied isolates (not shown in Figure 2) presented a unique multilocus genotype.
Isolates collected from COVID-19+ patients are heterogeneously scattered through
the dendrogram. Each one of these isolates presents a unique microsatellite multi-locus
genotype, as referred to above. Yet, in cluster #4, isolates VA388 and VA394 are closely
related, presenting a difference of only one repeat unit in one of the loci. Isolate VA382,
also from cluster #4, shares only one allele with VA388 and VA394 isolates, which are
genetically closer to CD257, an environmental isolate (sharing two alleles). Cluster #14
includes isolate VA392, which shares two alleles (STRAf 3A and 3B) with a non-COVID
respiratory product, VA378, which shows a difference of one repeat unit in STRAf 3C.
Isolates VA390 and VA394 were collected from the same patient (two days apart). These
isolates did not cluster together, and their multi-locus genotypes were completely different.
This can represent a mixed infection with two different strains at the same time, a fact that
is known to happen with A. fumigatus infections [34].
In other groups that do not include A. fumigatus isolates from patients positive for
COVID-19, it is possible to perceive that some clusters are formed by isolates with exactly
the same microsatellite multi-locus genotype: clusters #1 and #6 comprise four environ-
mental isolates each with the same genotype, and cluster #9 comprises four isolates from
respiratory samples also presenting the same genotype. Some other clusters, namely #2,
#3, #7, #11, and #16 also include genotypes that are not unique and are shared between
two or three isolates. The remaining isolates presented in Figure 2all showed a unique
genotype, even though some of them share one or two alleles with one or more isolates
(Supplementary Figure S1). Cluster #10 includes two isolates collected from animals that
are closely related and differ only in one allele.
J. Fungi 2023,9, 298 7 of 14
J. Fungi 2023, 9, x FOR PEER REVIEW 7 of 15
None of the genotypes of A. fumigatus isolates collected from COVID+ patients is common
to more than one isolate; they were all unique (Figure 1).
Figure 1. Minimum spanning tree constructed in Bionumerics 6.6. software (Applied Maths, bioMé-
rieux SA, Marcy-l'Étoile, France) using a categorical similarity coefficient and an unweighted pair
group method with arithmetic mean (UPGMA) analysis. The 85 different genotypes found are rep-
resented by each circle. The circle size is proportional to the number of isolates with each genotype.
Each color represents a different isolate source, as shown in the bottom left corner. Each line repre-
sents the distance between genotypes: solid bold line–1 marker; solid line–2 markers, and dotted
line–3 markers.
Figure 1.
Minimum spanning tree constructed in Bionumerics 6.6. software (Applied Maths,
bioMérieux SA, Marcy-l’Étoile, France) using a categorical similarity coefficient and an unweighted
pair group method with arithmetic mean (UPGMA) analysis. The 85 different genotypes found
are represented by each circle. The circle size is proportional to the number of isolates with each
genotype. Each color represents a different isolate source, as shown in the bottom left corner. Each
line represents the distance between genotypes: solid bold line–1 marker; solid line–2 markers, and
dotted line–3 markers.
J. Fungi 2023,9, 298 8 of 14
J. Fungi 2023, 9, x FOR PEER REVIEW 8 of 15
A dendrogram was also constructed (Supplementary Figure S1), and the most rele-
vant sections with the closest genetically related isolates are highlighted in Table 3. All the
other studied isolates (not shown in Figure 2) presented a unique multilocus genotype.
J. Fungi 2023, 9, x FOR PEER REVIEW 9 of 15
Figure 2. Groups of isolates showing genetic relatedness obtained from the dendrogram constructed
in Bionumerics 6.6. software (Applied Maths, bioMérieux SA, Marcy-l'Étoile, France) using a cate-
gorical similarity coefficient and an unweighted pair group method with arithmetic mean (UPGMA)
analysis. AC–air conditioner; EDC–electrostatic dust collector; BAL–bronchoalveolar lavage; BL–
bronchial lavage; H1 to H10 –hospitals’ ID (from where the isolates were collected); R–resistant to
azoles.
Isolates collected from COVID-19+ patients are heterogeneously scattered through
the dendrogram. Each one of these isolates presents a unique microsatellite multi-locus
genotype, as referred to above. Yet, in cluster #4, isolates VA388 and VA394 are closely
related, presenting a difference of only one repeat unit in one of the loci. Isolate VA382,
also from cluster #4, shares only one allele with VA388 and VA394 isolates, which are
genetically closer to CD257, an environmental isolate (sharing two alleles). Cluster #14
includes isolate VA392, which shares two alleles (STRAf 3A and 3B) with a non-COVID
respiratory product, VA378, which shows a difference of one repeat unit in STRAf 3C.
Isolates VA390 and VA394 were collected from the same patient (two days apart). These
isolates did not cluster together, and their multi-locus genotypes were completely differ-
ent. This can represent a mixed infection with two different strains at the same time, a fact
that is known to happen with A. fumigatus infections [34].
In other groups that do not include A. fumigatus isolates from patients positive for
COVID-19, it is possible to perceive that some clusters are formed by isolates with exactly
the same microsatellite multi-locus genotype: clusters #1 and #6 comprise four environ-
mental isolates each with the same genotype, and cluster #9 comprises four isolates from
respiratory samples also presenting the same genotype. Some other clusters, namely #2,
#3, #7, #11, and #16 also include genotypes that are not unique and are shared between
two or three isolates. The remaining isolates presented in Figure 2 all showed a unique
genotype, even though some of them share one or two alleles with one or more isolates
(Supplementary Figure S1). Cluster #10 includes two isolates collected from animals that
are closely related and differ only in one allele.
3.3. AfumID
The isolates enrolled in our study were included in the database AfumID (https://afu-
mid.shinyapps.io/afumID/ (accessed on 21 June 2022). Figure 3 shows how the COVID+
isolates take place among the ones already inserted in the database (A), and how the set
of all isolates of our study are scattered throughout the database (B). The orange dots cor-
respond to the susceptible isolates from the database, the blue dots represent the resistant
ones, and the black dots represent the isolates inserted by us in the database.
Figure 2.
Groups of isolates showing genetic relatedness obtained from the dendrogram con-
structed in Bionumerics 6.6. software (Applied Maths, bioMérieux SA, Marcy-l’Étoile, France)
using a categorical similarity coefficient and an unweighted pair group method with arithmetic
J. Fungi 2023,9, 298 9 of 14
mean (
UPGMA
) analysis. AC–air conditioner; EDC–electrostatic dust collector; BAL–bronchoalveolar
lavage; BL–bronchial lavage; H1 to H10 –hospitals’ ID (from where the isolates were collected);
R–resistant to azoles.
3.3. AfumID
The isolates enrolled in our study were included in the database AfumID (https://afumid.
shinyapps.io/afumID/ (accessed on 21 June 2022). Figure 3shows how the COVID+ isolates
take place among the ones already inserted in the database (A), and how the set of all
isolates of our study are scattered throughout the database (B). The orange dots correspond
to the susceptible isolates from the database, the blue dots represent the resistant ones, and
the black dots represent the isolates inserted by us in the database.
J. Fungi 2023, 9, x FOR PEER REVIEW 10 of 15
Figure 3. Representation of the isolates in this study (black dots) in the general population of the
AfumID database. The orange clade represents susceptible isolates. The blue clade represents re-
sistant isolates. (A). Set of isolates collected from COVID+ patients. (B). Set of all isolates in this
study.
4. Discussion
The rising relevance of Aspergillus fumigatus in human health has brought an increas-
ing interest in its epidemiology. The STRAf assay is a very useful tool to conduct genotyp-
ing studies due to its specificity, robustness, and high discriminatory power [32]. Isolates
collected from COVID positive patients, together with isolates from different sources,
were analyzed as described, and the genetic relationships between them were analyzed.
It was possible to observe a heterogeneous distribution of isolates among the different
sources. However, some of the isolates share one or two alleles with other isolates.
Figure 3.
Representation of the isolates in this study (black dots) in the general population of the
AfumID database. The orange clade represents susceptible isolates. The blue clade represents resistant
isolates. (A). Set of isolates collected from COVID+ patients. (B). Set of all isolates in this study.
J. Fungi 2023,9, 298 10 of 14
4. Discussion
The rising relevance of Aspergillus fumigatus in human health has brought an increasing
interest in its epidemiology. The STRAf assay is a very useful tool to conduct genotyping
studies due to its specificity, robustness, and high discriminatory power [
32
]. Isolates
collected from COVID positive patients, together with isolates from different sources, were
analyzed as described, and the genetic relationships between them were analyzed. It was
possible to observe a heterogeneous distribution of isolates among the different sources.
However, some of the isolates share one or two alleles with other isolates.
Analyzing the clusters highlighted in Figure 2, it is possible to conclude that those
containing isolates with exactly the same multi-locus genotype are mostly formed by
environmental isolates (clusters #1, #2, #3, and #6). However, cluster #9 is composed of
four respiratory samples presenting the same genotype. In contrast to what happens in
studies like the one performed by Guinea et al. [
35
] where environmental isolates usually
exhibit higher genetic diversity than respiratory ones, our environmental isolates presented
less diversity. This may be due to the fact that some of the environmental isolates were
recovered in the same spatial location or indoor environment, which might lead to a bias in
the obtained data.
When dealing with an environmental fungus capable of infecting both humans and
animals, and with a rising problem of resistance of environmental origin [
36
,
37
], it is also
important to better understand how isolates from these sources relate to each other. One
relevant observation in this study is the importance of Aspergillus fumigatus in the One
Health context. In the present study, isolates from different sources appeared to be closely
related, some of them with exactly the same genotypes. This is the case with isolates
HSMA34 and VA105 (cluster #7), an environmental and respiratory isolate, respectively,
isolates VA225 and VA290 (cluster #11) a human respiratory isolate, and an animal one
and isolates VA85 and VA95 (cluster #16), two isolates with known azole resistance, with a
respiratory and environmental origin, respectively. This observation will be crucial for the
implementation of measures to avoid the exposure of patients in healthcare facilities and
workers or occupants in other indoor settings.
Every isolate collected from a COVID+ patient presented a unique genotype. Some
of these isolates showed higher phylogenetic proximity to each other, more than with
other isolates collected from COVID negative patients. Cluster #4 includes two COVID+
isolates with only one repeat unit of difference in STRAf 3A locus–this might represent the
occurrence of a microvariation event, since both isolates were recovered in the same hospital,
but separated by months, and the detected variation occurs only in one marker [
38
]. VA382,
also from the same cluster, is more closely related to isolates collected from non-COVID+
patients, namely with an environmental isolate (CD257) and with an isolate collected from
a human respiratory specimen (VA221), sharing 2 alleles with each of them. Another cluster
with closely related isolates includes isolates collected from respiratory products from a
COVID+ patient (VA392) and isolates from a non-COVID patient (VA378). Both isolates
were collected from patients hospitalized in the same hospital and at the same time. This
cluster (#14), gathers two isolates that share two alleles and have a difference of one repeat
unit in the remaining allele, which might be a case of microvariation. Curiously, these
isolates (VA378 and VA392) have an especially high number of repeats in locus STRAf 3B.
A recent study by Steenwyk et al. [
39
] reveals that there are no significant differences in the
genome of COVID+ isolates and a reference strain used in that study. In our study, all the
other isolates collected from COVID+ patients were closely related to isolates from other
sources, sharing one or two alleles with them. The heterogeneity of genotypes displayed
supports the data presented previously by Mead [
40
]. Interestingly, two COVID+ isolates
(VA390 and VA394) were collected from the same patient but displayed totally different
multi-locus genotypes, which suggests that the patient was colonized at least by two
different strains, as previously referred to by other authors [34].
Even though none of the COVID+ isolates have the same multi-locus genotype in this
study, it is not surprising that some isolates present close genetic relationships, because
J. Fungi 2023,9, 298 11 of 14
almost all were obtained from patients in the same hospital, and therefore the patients
might have been exposed to the same contamination source. The study of Peláez-García
et al. [
41
] however, concluded that Aspergillus infections in COVID-19+ patients seem to be
community acquired, and not of nosocomial origin.
The inclusion of our isolates in the AfumID database allows us to understand the
placement of our isolates in the general population of the isolates that are included in
that database (Figure 3). This database is composed of the multi-locus genotypes of
4049 isolates collected all over the world, from environmental and clinical sources. The
database is composed of isolates susceptible to azoles, and others with known azole
resistance associated with the TR34/L98H and TR46/ Y121F/T289A mutations in the
cyp51A gene. Most of the resistant isolates are grouped in one clade of the database,
forming the resistant clade. It is possible to observe that most of the isolates of our
study are placed in the susceptible clade, but some of them are placed in the resistant
clade. It would be expected that isolates with known resistance (Supplementary Table S1)
caused by the TR34/L98H mutation would be grouped in this clade, which was observed.
Resistant isolates bearing other mutations were not all grouped in this clade, which could
be explained by the fact that this database was built with susceptible isolates and with
TR34/L98H resistant isolates [
33
]. The majority of the isolates without detected azole
resistance were grouped, as expected, in the susceptible clade, but some of them were
grouped in the resistant clade, which may be due to the presence of resistant isolates with
similar multi-locus genotypes.
Our study presented some limitations: almost all of the isolates collected from COVID+
patients were from the same hospital and this could represent a bias in our results. However,
since none of the isolates presented the same multi-locus genotype, this situation may
not represent a problem. The heterogeneity of genotypes among isolates collected from
COVID+ patients was also supported by Peláez-García et al. [
41
]. The small number of
isolates collected from COVID+ patients due to the lack of performed bronchoscopies [
18
]
is also a limitation that we could not overcome, since not all hospitals send their samples to
our laboratory.
5. Conclusions
To our knowledge, this was the first Portuguese study on Aspergillus fumigatus molec-
ular epidemiology that includes isolates retrieved from COVID-19 positive patients. Even
with a limited sample size, it was possible to perceive the heterogeneity of these isolates
through the determination of their microsatellite multi-locus genotypes, and a genotype
more frequently associated with SARS-CoV-2 infection does not appear to exist. This study
allowed us to understand more about the genetic relationships and position of isolates
collected from COVID+ patients in the background of other isolates collected in our country
over the years.
The possibility to perform multicentric studies with Aspergillus isolates from COVID+
patients from different hospitals throughout the country and to include other isolates
from more diverse sources will allow for the possibility to better understand Aspergillus
fumigatus interaction with SARS-CoV-2 infection and better manage the rising number of
aspergillosis cases, especially the ones linked with viral infections. Additionally, this will
allow sharing of preventive measures in different indoor environments to avoid exposure
to Aspergillus contamination.
Supplementary Materials:
The following supporting information can be downloaded at: https://
www.mdpi.com/article/10.3390/jof9030298/s1, Supplementary Table S1: Isolate characterization of
the isolates analyzed in the study; Supplementary Figure S1: Dendrogram obtained in the Bion-
umerics 6.6 software (Applied Maths, bioMérieux SA, Marcy-l’Étoile, France) using a categorical
similarity coefficient and an unweighted paired group method with arithmetic mean (UPGMA) for
the cluster analysis.
J. Fungi 2023,9, 298 12 of 14
Author Contributions:
Conceptualization, R.S.; methodology, S.M., D.C., C.V. (Cristina Veríssimo)
and R.S.; software, S.M.; validation, C.V. (Cristina Veríssimo) and R.S.; formal analysis, S.M., C.V.
(Cristina Veríssimo) and R.S.; investigation, S.M.; resources, C.T., H.S. and C.V. (Carla Viegas);
writing—original draft preparation, S.M.; writing—review and editing, C.T., D.C., C.V. (Carla Viegas),
C.V. (Cristina Veríssimo) and R.S.; supervision, R.S. All authors have read and agreed to the published
version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement:
The study was performed in accordance with the ethical
standards of the original Declaration of Helsinki and its later amendments, WHO’s Guidelines for
Good Clinical Practice and the Council of Europe’s Convention on Human Rights and Biomedicine.
A surveillance program on Aspergillus epidemiology and antifungal susceptibility approved by
National Health Institute of Ricardo Jorge is ongoing since 2012, and since the Aspergillus strains
used in this study belong to that culture collection and are completely anonymized, the study was
not submitted to the ethics committee’s approval. Since data regarding patients were requested in a
later phase of the revision process and were not included in the initial manuscript submission, the
approval of the Health Ethics Committee of the Hospital is pending.
Informed Consent Statement:
Patient consent was waived due to this study’s compliance with total
anonymity, while being of paramount interest for public health concerns. The Aspergillus strains used
in this study belong to a culture collection from the National Institute of Health and are completely
anonymized, without any access to patient ID.
Data Availability Statement:
Data presented in this study is not publicly available due to privacy
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
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