ArticlePDF Available

Stably transmitted defined microbial community in honeybees preserves Hafnia alvei inhibition by regulating the immune system


Abstract and Figures

The gut microbiota of honeybees is highly diverse at the strain level and essential to the proper function and development of the host. Interactions between the host and its gut microbiota, such as specific microbes regulating the innate immune system, protect the host against pathogen infections. However, little is known about the capacity of these strains deposited in one colony to inhibit pathogens. In this study, we assembled a defined microbial community based on phylogeny analysis, the ‘Core-20’ community, consisting of 20 strains isolated from the honeybee intestine. The Core-20 community could trigger the upregulation of immune gene expressions and reduce Hafnia alvei prevalence, indicating immune priming underlies the microbial protective effect. Functions related to carbohydrate utilization and the phosphoenolpyruvate-dependent sugar phosphotransferase system (PTS systems) are represented in genomic analysis of the defined community, which might be involved in manipulating immune responses. Additionally, we found that the defined Core-20 community is able to colonize the honeybee gut stably through passages. In conclusion, our findings highlight that the synthetic gut microbiota could offer protection by regulating the host immune system, suggesting that the strain collection can yield insights into host-microbiota interactions and provide solutions to protect honeybees from pathogen infections.
Content may be subject to copyright.
Frontiers in Microbiology 01
Stably transmitted defined
microbial community in
honeybees preserves Hafnia alvei
inhibition by regulating the
immune system
Jieni Wang
1, Haoyu Lang
1, Wenhao Zhang
2, Yifan Zhai
3,4, Li
3,4, Hao Chen
3,4, Yan Liu
3,4 and Hao Zheng
1 College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China,
2 Faculty of Agriculture and Food, Kunming University of Science and Technology, Kunming, China,
3 Shandong Academy of Agricultural Sciences, Institute of Plant Protection, Jinan, China, 4 Key
Laboratory of Natural Enemies Insects, Ministry of Agriculture and Rural Aairs, Jinan, China
The gut microbiota of honeybees is highly diverse at the strain level and
essential to the proper function and development of the host. Interactions
between the host and its gut microbiota, such as specific microbes regulating
the innate immune system, protect the host against pathogen infections.
However, little is known about the capacity of these strains deposited in
one colony to inhibit pathogens. In this study, we assembled a defined
microbial community based on phylogeny analysis, the ‘Core-20’ community,
consisting of 20 strains isolated from the honeybee intestine. The Core-20
community could trigger the upregulation of immune gene expressions
and reduce Hafnia alvei prevalence, indicating immune priming underlies
the microbial protective eect. Functions related to carbohydrate utilization
and the phosphoenolpyruvate-dependent sugar phosphotransferase system
(PTS systems) are represented in genomic analysis of the defined community,
which might be involved in manipulating immune responses. Additionally,
we found that the defined Core-20 community is able to colonize the
honeybee gut stably through passages. In conclusion, our findings highlight
that the synthetic gut microbiota could oer protection by regulating the host
immune system, suggesting that the strain collection can yield insights into
host-microbiota interactions and provide solutions to protect honeybees
from pathogen infections.
Apis mellifera, colonization resistance, Hafnia alvei, immune system, gut microbiota
e host intestinal tract is a complex ecosystem oering niches for benecial symbionts
that aid in food digestion and disease resistance (Engel and Moran, 2013b; Pereira and
Berry, 2017). Imbalanced gut microbiota driven by the antibiotic treatment could lead to
metabolism changes, potentially pathogenic bacteria blooming, epithelial barrier
TYPE Original Research
PUBLISHED 01 December 2022
DOI 10.3389/fmicb.2022.1074153
Jun-Bo Luan,
Shenyang Agricultural University, China
Guan-Hong Wang,
Chinese Academy of Sciences (CAS), China
Xiaoli Bing,
Nanjing Agricultural University,
Hong-Wei Shan,
Ningbo University, China
Hao Zheng
This article was submitted to
Microbial Symbioses,
a section of the journal
Frontiers in Microbiology
RECEIVED 19 October 2022
ACCEPTED 14 November 2022
PUBLISHED 01 December 2022
Wang J, Lang H, Zhang W, Zhai Y, Zheng L,
Chen H, Liu Y and Zheng H (2022) Stably
transmitted defined microbial community
in honeybees preserves Hafnia alvei
inhibition by regulating the immune
Front. Microbiol. 13:1074153.
doi: 10.3389/fmicb.2022.1074153
© 2022 Wang, Lang, Zhang, Zhai, Zheng,
Chen, Liu and Zheng. This is an open-
access article distributed under the terms
of the Creative Commons Attribution
License (CC BY). The use, distribution or
reproduction in other forums is permitted,
provided the original author(s) and the
copyright owner(s) are credited and that
the original publication in this journal is
cited, in accordance with accepted
academic practice. No use, distribution or
reproduction is permitted which does not
comply with these terms.
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 02
disruption, and increased susceptibility to infections (Bue etal.,
2015; Raymann etal., 2017; Fünaus etal., 2018; Lang et al.,
2022). erefore, the gut microbiota can preclude infections of
enteric pathogens, which is one of the most widespread benets
to its host (Spees etal., 2013; Kim etal., 2017). Considering the
complexity of interactions between the microbiota and the host,
the underlying basis of this protection, or ‘colonization resistance,
is still insuciently understood.
Honeybees (Apis mellifera) harbor about ve core host-
specic bacterial genera, which probably have co-evolved with
social bees for over 80 million years (Koch etal., 2013; Kwong and
Moran, 2016). ey include Snodgrassella, Gilliamella,
Bidobacterium, Bombilactobacillus Firm-4, and Lactobacillus
Firm-5 (Martinson et al., 2011; Kwong and Moran, 2016).
Additionally, the genus Apilactobacillus, Frischella,
Commensalibacter, Bartonella, and Bombella are less prevalent,
which occupy particular niches and engage in host health
maintenance (Engel etal., 2016; Liu etal., 2022). With relatively
simple gut microbiota, honeybees present opportunities to
investigate gut community dynamics and host–microbe
interaction as an experimental system (Zheng etal., 2018). Recent
research has demonstrated the honeybee gut microbiome
contributes to metabolism, development, and protection against
pathogens (Engel etal., 2016; Raymann and Moran, 2018). Some
species belonging to Bombilactobacillus Firm-4, Lactobacillus
Firm-5, and Bidobacterium can inhibit the growth of other
microorganisms in vitro (Forsgren etal., 2010; Vásquez etal.,
2012; Butler etal., 2013; Killer etal., 2014). Members of bee gut
microbiota, such as Snodgrassella alvi and Gilliamella apis, could
lower gut lumen pH and oxygen levels (Zheng et al., 2017),
compete for nutrients (Martinson etal., 2012; Wu etal., 2021), and
antagonize with type VI secretion system (Steele etal., 2017) to
inhibit pathogen virulence and growth.
e colonization resistance conferred by the gut microbiota
through stimulating the host’s innate immune system was
supported by increasing evidence (Lawley and Walker, 2013). e
innate immune system of honeybees comprises the Toll and Imd
pathways (Lourenço etal., 2013, 2018; Danihlík et al., 2015),
which primarily regulate the production of antimicrobial peptides
(AMPs), such as abaecin, apidaecin, defensin, and hymenoptaecin,
during pathogen infection (Evans etal., 2006; Guo etal., 2021).
When honeybees were colonized with conventional gut
microbiota or mono-colonized with strains from S. alvi, the
immune system of honeybees was stimulated to inhibit potential
pathogens such as Serratia marcescens (Horak et al., 2020).
However, substantial strain-level diversity was found within the
bee gut microbiota, where individual strains harbor unique genes
and distinct functional capabilities (Ellegaard etal., 2019; Brochet
et al., 2021; Lang et al., 2022). In addition to understanding
individual strains involved in interactions determining
colonization resistance, how bacterial combinations by multiple
strains from dierent species control colonization resistance still
need to beinvestigated.
Hafnia alvei, a specic pathogen in bees, could cause
septicemia with a mortality rate of over 90% by injection and
inammation of the intestinal tract by oral (Møller, 1954; Erban
etal., 2017; Grabowski and Klein, 2017). Leveraging previous
work, Lactobacillus apis W8171 could inhibit H. alvei infection
and prevent severe mucosal architecture damage in the honeybee
rectum (Lang et al., 2022). In this study, we established a
consortium based on phylogeny analysis, the ‘Core-20’
community, consisting of 20 strains isolated from the honeybee
intestine that provide colonization resistance against H. alvei.
Interestingly, the higher complex and biodiversity community
displays advantages in promoting the expression of regulators and
AMPs of the immune system. e comparative genomic analysis
revealed that the phosphoenolpyruvate-dependent sugar
phosphotransferase system (PTS system) could potentially
be involved in manipulating immune responses. In addition,
wetransmitted the Core-20 community for four passages and
found that the Core-20 could colonize steadily. us, the Core-20
community serves as a stable and functional microbiota that can
beused for detailed investigation of host-microbe and microbe-
microbe interactions in honeybees.
Materials and methods
Characterization of stains in the Core-20
community designed by the phylogeny
of honeybee gut microbiota
To establish dened minimal microbiota that recapitulates
healthy honeybee gut microbiota stably and functionally, the
integral intestine homogenization of conventional honeybee was
cultured on a rich, non-selective culture medium. About 110
strains were mono-cloned and identied by whole genome
sequencing (WGS), representing conventional bacterial strains.
e quality-controlled reads were assembled with the
SOAPdenovo2 genome assembler. e completeness and
contamination of genomes were assessed by CheckM (>96%
completeness, <0.6% contamination). Phylogenetic analysis by
WGS shows that strains assorted into dierent clusters according
to gANI identities referred to as species-level (Su etal., 2021; Wu
etal., 2021). Six strains representing the six most prevalent and
abundant genera of honeybee gut microbiota are selected for a
bacterial consortium named “Core-6,” and 20 strains at the
species-level form “Core-20” bacterial community (Figure1).
Within the Proteobacteria phylum, four members of the
Core-20 community were assigned to the genus Gilliamella, one
strain to Snodgrassella, and three strains to Bartonella. Two abundant
species clusters in the Firmicutes phylum are Bombilactobacillus
Firm-4 and Lactobacillus Firm-5, including two strains and four
strains, respectively. Additionally, Apilactobacillus kunkeei, which
proved its ability to protect honeybees from pathogens, was added
as an essential functional part (Daisley etal., 2020a,b).
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 03
Composition of honeybee gut microbiota and strains of the Core-20 and Core-6 community. (A) Maximum-likelihood tree inferred by GTDB-tk
based on the amino acid sequences of bacterial marker genes. (B) Detailed information on strain classification and grouping. The Core-6
community consists of six strains representing the six most prevalent and abundant genera of honeybee gut microbiota, and the Core-20 is
composed of 20 strains at the species level. Rounds mark the strains of the Core-20, triangles mark the members of the Core-6 and stars mark
strains used in the mono-colonization experiments. Color bars indicate the classification of honeybee gut microbiota.
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 04
Bacterial strains were isolated from the guts of A. mellifera and
stored at –80°C with 25% (v/v) glycerol PBS solution. e glycerol
stocks were plated on heart infusion agar supplemented with 5%
(vol/vol) debrinated sheep’s blood (Solarbio, Beijing, China),
MRS agar (Solarbio, Beijing, China) or TPY agar (Solarbio,
Beijing, China) incubated at 35°C in 5% CO2 for 2–3 days. e
culture conditions of strains used in this study were described by
Wu et al. (2021). Conrmed by PCR with universal bacterial
primers 27F (5-AGAGTTTGATCCTGGCTCAG-3) and 1492R
(5-TACGACTTAACCCCAATCGC-3), individual strains were
mixed with 25% glycerol PBS solution. e dened bacterial
communities were generated by mixing equal volumes of bacterial
suspensions with adjusted OD600 = 1.
Honeybee collection, containment, and
Microbiota-free (MF) bees were obtained as described by
Zheng et al. (Zheng etal., 2018). All bees were kept in an
incubator (35°C, RH 50%). For the H. alvei challenging
experiment, newly emerged MF bees (Day 1) were divided into
several groups, with 25 MF bees in one cup cage. For each
colonization group, bees lived on the 1 ml bacterial suspensions
mixed with 1 ml sucrose solution (50%, w/v) and 0.5 g sterilized
pollen for 24 h. For the MF group, 1 ml of 1 × PBS was mixed with
1 ml of sucrose solution (50%, w/v) and 0.5 g sterilized pollen.
Aer 24 h inoculation, all groups were fed regular diets, sucrose
solution (50%, w/v), and sterilized pollen. To precisely control the
infection amount of H. alvei cells, bees from the colonization and
MF groups were all orally inoculated with H. alvei SMH01
individually on Day 7 (Lang etal., 2022). Aer ve-day regular
diets, the load of H. alvei was determined by qPCR.
For inoculation and sampling in passaging line, newly
emerged MF bees (Day 1) were randomly assigned to three cups
and living on the 1 ml the Core-20 bacterial suspension mixed
with 1 ml sucrose solution (50%, w/v) and 0.5 g sterilized pollen
for 24 h, with 25 MF bees in one cup cage. Five days aer the nal
oral inoculation, the whole gut of each bee was sampled,
immediately placed into a sterile 1.5 ml tube individually, and
ground with sterile 25% glycerol PBS solution. ree guts from
each cup were pulled together to prepare inoculation for the
following passage, and the other guts were stored at 80°C for
DNA extraction and sequencing.
16S rRNA gene amplicon sequencing and
DNA was extracted from gut homogenates using the CTAB
method (Powell et al., 2014; Zheng et al., 2018). Targeted
amplicons of the V3-4 region of the 16S rRNA gene were
generated with primers 341F and 806R (Caporaso etal., 2011).
Sequencing libraries were generated with NEBNext Ultra II DNA
Library Prep Kit for Illumina (New England Biolabs, Ipswich,
UnitedStates). ey were sequenced at Novogene Bioinformatics
Technology Co. Ltd., Beijing, China, on the Illumina NovaSeq6000
platform (2 × 250 bp). Bioinformatic analysis was implemented
using Mothur (version 1.40.5; Schloss etal., 2009; Kozich etal.,
2013; Schloss, 2020). Aer primer trimming and quality control,
sequences were split into groups corresponding to their taxonomy
at the level of species and then assigned to operational taxonomic
units (OTUs) at a 1% dissimilarity level based on the reference
database consisting of aligned 16S rRNA sequences of our 20
strains (Supplementary Figure S1; Xue et al., 2019). Relative
abundances were then calculated based on the read numbers.
Principal coordinates analysis (PCoA) and alpha diversity indices
were visualized in R (version 3.6.1). Raw sequence reads have been
deposited at the NCBI SRA database under the BioProject
accession number PRJNA891025.
Quantitative PCR of bacterial 16S rRNA
genes and immune-related genes
DNA was extracted from gut homogenates using the CTAB
method (Powell etal., 2014; Zheng etal., 2018). DNA concentration
was determined with the Qubit 4 Fluorometer (ermo Fischer
Scientic; Waltham, MA, UnitedStates). H. alvei loads and immune-
related gene expressions were determined by qPCR using the
ChamQ Universal SYBR qPCR Master Mix (Vazyme Biotech,
Nanjing, China). Primer sets specic to H. alvei and immune-related
genes are listed in Supplementary Table S1 (Horak etal., 2020; Lang
etal., 2022). e primers of spaetzle 4 (Spz4; XM_028668966.1)
were designed based on the nucleotide sequence available in
GenBank: forward 5-CAACGAATTCAGGGACGAGG-3, reverse
5-AGTAGTGCCGGGGAAATTCA-3. All qPCRs were performed
in 96-well microplates on a QuantStudio 1 real-time PCR system
(ermo Fischer Scientic). Melting curves were generated aer
each run (95°C for 15 s, 60°C for 20 s, and increments of 0.3°C until
reaching 95°C for 15 s). Each reaction was performed in triplicates
on the same plate. e data was analyzed using the QuantStudio
Design and Analysis Soware. Aer calculating gene copies,
normalization was performed to reduce the eect of gut size
variation and extraction eciency using the host’s actin gene
(Kešnerová etal., 2020).
Functional genomics analysis
Input les were assembled and annotated genomes of the
Core-20 (Su etal., 2021; Wu etal., 2021). H. alvei reference protein
sequence (GCF_011617105.1) was downloaded from NCBI and
annotated by KAAS1 (Moriya etal., 2007). Articial metagenomes
were created by merging the contigs of each genome into a
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 05
multi-fasta le (Brugiroux et al., 2016). KEGG mapping was
performed using the online version
(Kanehisa etal., 2022). e
comparison and analysis of orthologous clusters among genomes
were performed at3 (Xu etal., 2019).
Statistical analysis
Statistical analysis was performed using one-way ANOVA
(ANalysis Of VAriance) with post-hoc Tukey HSD (honestly
signicant dierence) using package “multcomp” in R (version
3.6.1). p-value of less than 0.05 (two-tailed) was considered
statistically signicant (*p < 0.05, **p < 0.01, ***p < 0.001).
Resistance of the Core-20 community
against honeybee opportunistic
pathogen Hafnia alvei
To evaluate the potential of the dened communities to
protect against H. alvei infection, we rst colonized MF
honeybees with the Core-20, the Core-6, and strains from the
genus Snodgrassella, Bartonella, Bombilactobacillus Firm-4,
Apilactobacillus and Bidobacterium (Figure1). At Day 7, all
honeybee were orally infected with H. alvei individually
(106 CFU per bee; Figure 2A). Successful microbiota
colonization was conrmed by 16S rRNA gene V3-V4 amplicon
sequencing at Day 12. Compositional analysis showed that
observed species in the Core-20, compared to the Core-6, were
increased, and the relative abundance of each taxonomy group
diers (Figure2B). Strains W8131, B14384H2 and W8123 from
the genus Gilliamella and strains W8093, W8171, and W8173
from the genus Lactobacillus Firm-5, which are specic to the
Core-20, exhibit substantial improvement in species
abundances, showing their tness in honeybee gut environment
and ability to coexist with the complex bacterial community.
Aer 5 days of infection, H. alvei loads were measured by
qPCR. Among mono-colonized bees, only B. choladocola
B10834H15 and B. choladohabitans W8113 signicantly inhibited
the growth of H. alvei invivo compared with the MF group at Day
12 (Figure2C). According to our previous research, H. alvei loads
in the bees with L. apis W8172, and Gilliamella apicola W8136
(the same species as G. apicola B14384G12) were also signicantly
lower than MF bees (Lang etal., 2022). Interestingly, bees treated
with the Core-6, including all these strains demonstrating the
ability to inhibit pathogens, did not show a signicant reduction
of H. alvei, while the Core-20 reduced the H. alvei loads by 78
times. Taken together, the presence of particular species did
inhibit H. alvei. Still, this microbiota-induced prevention of
pathogen infection possibly changes with the gut microbiota
composition, suggesting a complex dynamic balance between
microbe-host and microbe-microbe interaction.
Immune expression response induced by
the defined community
Intestinal homeostasis maintenance depends on dynamic
interactions between gut bacteria and the host’s innate immune
systems (Yoo et al., 2020). Commensal gut microbiota could
prevent pathogen colonization and infection by enhancing the
mucosal barrier and promoting innate immune responses. e gut
microbial symbionts of the honeybee can induce antimicrobial
immune responses in the host, like AMPs (Kwong etal., 2017).
We assessed the relative expression of genes from Toll and Imd
pathways by qPCR 24 h following inoculation with the Core-20 and
Core-6. e Toll and Imd pathways include the receptors (spz4,
toll; pgrp-lc), the regulators (cactus; dredd), and the transcription
factors (dorsal; relish), respectively. On Day 2, bees colonized with
the Core-20 signicantly upregulated pgrp-lc, dredd, and relish
from the Imd pathway as well as toll and cactus-2 from the Toll
pathway relative to MF bees (Figure3A). Furthermore, wefocused
on the expression of genes encoding AMPs, and remarkably,
we discovered that bees with the Core-6 exhibited a notable
reduction of AMPs abaecin, apidaecin, hymenoptaecin and
defensin-1 (Figure3B), which might indicate an immunosuppressive
ability of the Core-6. To nd out whether the Core-20 could
consistently upregulate host-producing AMPs in response to
H. alvei infection, the expression of AMPs genes was measured
again on Day 7, right before H. alvei inoculation. Interestingly, bees
with the Core-20 showed a signicant increase of AMPs abaecin,
apidaecin, hymenoptaecin, and defensin-1 (Figure3C), indicating
abilities of the Core-20 to stimulate innate immune response
preventing the colonization by pathogenic H. alvei.
Our ndings showed the Core-6 community exhibited
diminished production of antimicrobial peptides, while the
Core-20 community upregulated the host immune system,
including regulators in innate immune pathways and AMPs
expression. Apidaecin, the most susceptible AMP against H. alvei
invitro (Lang etal., 2022), expressed much higher in the Core-20
condition. Overall, our ndings suggested that a primary
mechanism by which Core-20 provides colonization resistance is
that it can trigger host immune responses.
Potential to regulate host immune
system through
phosphoenolpyruvate-dependent sugar
phosphotransferase system
Protection against H. alvei by the Core-20 community supports
immune regulation as a factor in pathogen defense. To gain insights
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 06
into the potential functional capabilities of the Core-20 to activate
immunologic responses, wesequenced and annotated the individual
genomes of the 20 strains and mapped the predicted protein
sequences against the KEGG database. Articial metagenomes of the
Core-6 and Core-20 were generated by merging the contigs of
individual strains. e presence and completeness of KEGG modules
were determined for individual genomes of 20 strains, the Core-6
and Core-20 (Figure4). Aer hierarchical clustering, weobserved
dierent functional groups depending on their phylogenetic
relatedness incidentally. e majority of strains share highly
conserved modules, including phosphate acetyltransferase-acetate
kinase pathway (M00579), PRPP biosynthesis (M00005), F-type
ATPase (M00157), various carbohydrate metabolism pathways and
multiple amino-acid and nucleoside biosynthesis pathways.
Additionally, modules more prominent in Gilliamella strains
comprised pyridoxal-p biosynthesis (M00916) and carbohydrate
degradation modules, such as ascorbate, D-glucuronate, and
D-galacturonate (M00550, M00061, M00631). We also found
Core-20 leads to protection against oral H. alvei infection. (A) Experimental design for honeybees colonized with specific microbes challenging
with H. alvei. (B) Relative abundance of the Core-6 and Core-20 community on Day 12. 16S rRNA V3-V4 amplicons were sequenced and
analyzed, showing successful microbiota colonization and composition dierences between the Core-6 and the Core-20. (C) Absolute
abundance of H. alvei in dierent treatment groups 5 days post-infection. Single strains, such as B. choladocola B10834H15 and B.
choladohabitans W8113, significantly inhibited the growth of H. alvei. The Core-20 community, which is much more complex than the Core-6,
significantly reduced the H. alvei loads.
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 07
nucleotide sugar biosynthesis (M00554), galactose degradation
(M00632), and beta-oxidation (M00086) modules enriched in
Bidobacterium strains. In total, the comparison of the Core-6 and
Core-20 shows functional similarity. However, there were still several
modules enriched in the Core-20, including cobalamin anaerobic
biosynthesis (M00924), beta-oxidation (M00087), propanoyl-CoA
metabolism (M00741), d-galactonate degradation(M00552), pectin
degradation (M00081), and hydroxyproline degradation (M00948).
Additionally, wealso estimated the complement of KEGG modules
for the genome of H. alvei, and we found highly overlapping
functions with the Core-20 community, indicating its tness and
potential virulence. At the same time, several pathways were found
enriched in H. alvei, such as glycogen biosynthesis (M00854),
undecaprenylphosphate alphaL Ara4N biosynthesis (M00761),
fumarate reductase (M00150), cysteine biosynthesis (M00338),
menaquinone biosynthesis (M00116), ubiquinone biosynthesis
(M00117), and multiple pathways of biotin biosynthesis. Overall,
wespeculated that receptors or products from carbohydrate, fatty
acid, and amino acid metabolism could probably display a key role
in regulating the immune system.
Next, weinvestigated the genes specic to the Core-20 but not
present in the Core-6, potentially associated with the capacity to
trigger the immune system. e comparative analysis found that
3,206 genes unique to the Core-20 were enriched in 1,231 Gene
Ontology clusters (Figure5A). Notably, the enriched GO among
all identied clusters was the phosphoenolpyruvate-dependent
sugar phosphotransferase system (PTS, GO:0009401), a complex
enzyme system functioning in the detection, transport, and
phosphorylation of various sugar substrates (Kotrba etal., 2001;
Gabor et al., 2011). e PTS is comprised of two general
cytoplasmic components, enzyme I(EI) and histidine phosphoryl
carrier protein (HPr), and membrane-bound sugar-specic
multidomain enzymes II (EII). Each EII complex consists of one
or two hydrophobic integral membrane domains (domains C and
D) and two hydrophilic domains (domains A and B; Figure5B).
Mannose/fructose/sorbose family PTS system was observed, and
four genes, including EIIAB, EIIB, EIIC, and EIID, were shared in
four strains from the genus Lactobacillus Firm-5 (Figure 5C).
Interestingly, W8173, W8093, and W8171, three stains specic to
the Core-20, harbored their unique clusters of EIIA, EIIB, EIIC,
and EIID (Figure5D). Taken into account that both IIC and IID
components of the mannose phosphotransferase system are
involved in recognition of antimicrobial peptides (Kjos etal., 2010;
Zhou etal., 2016), our results indicated that membrane-bound EII
of phosphotransferase system could probably trigger an immune
response, causing protection in the Core-20 bees.
Stability transmission of Core-20
community during successive passaging
in vivo
Due to the potential of the Core-20 to inhibit pathogens and
shape the host immune system, wewonder whether the Core-20
Core-20 triggers host immune gene expression in Imd and Toll pathways (A,B) at 24  h post-colonization and (C) 7  days post-colonization. The
Core-20 displayed a significant promotion in regulators of the Toll and Imd pathways on Day 2 and potential ongoing upregulation in AMPs
expression on Day 7. Besides, the Core-6 significantly reduced the expression of AMPs on Day 2. All results indicated that the gut microbiota could
stimulate the host’s innate immune system. Gene expression was normalized relative to the housekeeping gene actin. *p< 0.05; **p< 0.01 (Tukey
honest method).
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 08
community can stably colonize the honeybee gut over several
passages. Microbiota-free bees were inoculated with the frozen
mixtures of the Core-20 colony and sampled the whole gut on
Day 7. e gut microbiota was mixed and passed on throughout
four passages: passage 1 (P1), P2, P3, and P4. At the end of each
passage, bacterial communities were sequenced by amplicon
The presence and completeness of KEGG modules analysis of individual strains, the Core-6, and the Core-20 community. A hierarchical clustering
heat map of KEGG module distribution in the draft genomes and artificial metagenomes. The comparison of the Core-6 and Core-20 shows
functional similarity. Wealso found highly overlapping functions between H. alvei and the Core-20 community, indicating its fitness and potential
virulence. The color code indicates the presence and completeness of each KEGG module, expressed as a value between module complete (dark
blue) and module absent (white).
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 09
sequencing of the variable regions 3 and 4 of the 16S rRNA gene
(Figures6A,B). All strains except G. sp. W8131 were detected
individually in bee gut samples among passages, indicating W8131
either is below the detection limit or does not colonize. e relative
abundance of Bidobacterium, Snodgrassella, and Apilactobacillus
increased during passaging. Notably, G. apicola W14384G12 and
L. melliventris W8171 were dominant within their genus,
respectively. e relative abundance of Bartonella was maintained
at a relatively stable level during transmission, suggesting the
restriction and regulation of honeybee hosts to gut microbiota.
We also found an overall decrease in alpha diversity over time
across the four passages (Figure6C, Tukey honest method, p < 0.05
for P1-P4, P2-P4) and a signicant dierence between P1 and the
other passages in beta-diversity measured by Bray–Curtis
dissimilarity (Figure 6D, PERMANOVA, p = 0.013 for P1-P2,
p = 0.004 for P1-P3, p = 0.001 for P1-P4). Our ndings indicated
that strains of the Core-20 community display stable coexistence
aer slight uctuations in species abundances and biomass during
P1. In summary, these data suggest that the Core-20 community
maintains stability despite uctuations over the course of passage.
While early culture-based studies demonstrated that honeybee
gut symbionts could becultured in vitro, induce host immune
response, and confer protection against pathogens aer inoculation,
little is known about the capacity of these isolates deposited in one
colony. In this study, weassembled a dened microbial consortium
of honeybees (the Core-20 community) based on the phylogeny
analysis, which strongly inhibits H. alvei. Following exposure,
H. alvei can grow to high loads (109 CFU per gut), produce
inammatory reactions, and potentially result in host mortality.
We focused on the expansion of H. alvei infection, which is
primarily inuenced by the gut microbiota, and carried out
comprehensive investigations on the mechanism of colonization
resistance by the gut microbiota. e Core-20 community could
trigger upregulation of AMPs and precise H. alvei prevalence,
indicating immune priming underlies part of the dened
community protective eect. Functions related to carbohydrate
utilization and the PTS system were represented in genomic analysis
of the Core-20 community, which might play a role in immune
The PTS system enriched in the Core-20 community might trigger the immune response oering protection. (A) The Venn diagram was generated
using OrthoVenn2. Results showed the number of shared orthologous clusters of protein-coding genes between artificial metagenomes.
(B) Diagrammatic representation of the bacterial phosphotransferase signal transduction pathway (Mannose/fructose/sorbose family PTS system
as an example). General phosphoryl and sugar transport reaction catalyzed by the PTS. Sugars are transported and concomitantly phosphorylated
by the PTS. (C,D) In the genus Lactobacillus Firm-5, gene loci of mannose/fructose/sorbose family PTS system (C), shared in 4 strains or (D),
unique to strains in the Core-20. Homologous genes are connected by gray bars. Wefound that W8173, W8093, and W8171, three stains specific
to the Core-20, harbored their unique clusters of EIIA, EIIB, EIIC, and EIID, indicating that membrane-bound EII of phosphotransferase system
could probably trigger an immune response.
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 10
system stimulation. Additionally, we found that the Core-20
community is able to colonize the honeybee gut over four passages
stably. Our ndings highlight a dened microbial community could
oer protection via host–microbe interaction (for example,
regulating the host immune system), suggesting that the Core-20
community could beused for gut microbiota research in honeybees.
A major function of the stable gut microbiota is to provide
colonization resistance, preventing pathogens from colonizing and
causing long-term infection and even mortality. Ghimire et al.
identied Clostridioides dicile-inhibiting strains through single
strain versus pathogen coculture assays in vitro. However, when they
came to investigate how changes in the combinatorial assembly of
bacteria might aect the inhibition capacity, their results
demonstrated that new phenotypes masking the individual strain
phenotype could emerge depending on the composition of the mix.
For instance, bacterial consortia, where all the strains individually
showed inhibition, display the enhancement of C. dicile growth
(Ghimire etal., 2020). Moreover, germ-free mice colonized with
The Core-20 community stably colonized honeybees for four passages. (A) Experimental design for passaging transmission. (B) Relative
abundance of strains in the Core-20 during four passages. All strains except G. sp. W8131 were detected individually in bee gut samples among
passages. (C) Box plots of Shannon’s alpha diversity index at each passage. Results showed a slight decrease in alpha diversity. (D) Principal
coordinates analysis (PCoA) plot of Bray–Curtis dissimilarity among samples. Wefound that the last three passages showed community similarity
except for P1.
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 11
members of the altered Schaedler ora (ASF), a bacterial consortium
consisting of eight mouse-derived strains, provided insucient
colonization resistance to Salmonella enterica serovar
Typhimuriumthe. However, enforced with three facultative
anaerobes in Oligo-MM12 mice prevent infection completely
(Brugiroux etal., 2016). Here, B. choladocola B10834H15 from
Bartonella and B. choladohabitans W8113 from Bidobacterium
signicantly inhibited the growth of H. alvei. In previous studies,
Bidobacterium of honeybees could produce antimicrobial
substances in vitro to inhibit other microorganisms, contributing to
the resistance of pathogenic bacteria for the host (Forsgren etal.,
2010; Vásquez etal., 2012; Butler etal., 2013). In addition, Bombella
apis has been evidenced to benet the larval development of honey
bees and protect larvae against fungal pathogens (Liu etal., 2022).
Notably, the Core-6 community could increase the growth of
H. alvei. In contrast, single strains and the Core-20 eectively
inhibited H. alvei (Figure2C), demonstrating that a dened bacterial
community could oer the inhibition capacity as individual strains.
e microbe-microbe interaction needs to be concerned with
designing dened pathogen-inhibiting bacterial mixtures in vivo.
e mechanisms that regulate the ability of the microbiota to
restrain pathogen growth are complex, including induction of host
immune responses, localization to intestinal niches, and
competitive metabolic interactions (Kamada etal., 2013). AMPs
can maintain gut microbiota homeostasis by selectively inhibiting
foreign bacteria and keeping native symbionts from over-
proliferating (Kwong etal., 2017). e synthesis and secretion of
AMPs is a highly regulated process, mainly controlled by the Toll
and Imd pathways (Lourenço etal., 2013, 2018; Danihlík etal.,
2015). Specic gut symbionts, such as S. alvi, A. kunkeei, Frischella
perrara, and L. apis, have been conrmed to induce honeybee
innate immune response. ey upregulate the Toll and Imd
pathway, leading to AMPs expression (Emery etal., 2017; Daisley
et al., 2020b; Lang etal., 2022). Considering that the Core-6
consisted of microbes that were able to induce the immune
response, the whole gut microbiota balance composition could
bemore important for regulating the immune system. e Core-20,
a high-species-diversity colony, had more signicant upregulation
of the immune regulatory genes and AMPs genes encoding
abaecin, apidaecin, hymenoptaecin, and defensin-1 (Figure 3),
suggesting the ability of the Core-20 community in stimulating
host innate immune system through their regulators and eectors.
Biolm and the outer membrane protein, such as the S-layer
protein unique to L. apis W8172, could bepotential drivers of the
host immune response. Weused KEGG modules to character gene
sets linked to specic metabolic capacities and OrthoVeen2 to
compare and annotate orthologous gene clusters among multiple
genomes (Figures4, 5). Results showed that the PTS system was
signicantly enriched in the Core-20 community. e PTS system
is a highly conserved phosphotransfer cascade whose components
modulate many cellular functions in response to carbohydrate
availability (Houot etal., 2010). Previous studies have elucidated the
importance of bacterial PTS system for honeybees, including
detoxifying specic nectar components (Engel and Moran, 2013a),
nutrient metabolic transformations (Lee etal., 2015), and adaptation
to the diet and gut environment of the honeybee. PTS system of
Enterococcus faecalis could increase proinammatory cytokine
secretion by colon tissue and macrophages to enhance colonization
in mice (Fan etal., 2019). Besides, the PTS system of Vibrio cholerae
display control of carbohydrate transport and activation of biolm
formation on abiotic surfaces (Houot etal., 2010). Additionally, EIIC
and EIID from the mannose/fructose/sorbose family PTS system,
the membrane-banding proteins, is responsible for specic targeting
by antimicrobial peptides, indicating their potential to regulate the
immune system (Diep etal., 2007; Kjos etal., 2010; Zhou etal., 2016).
According to Rolf Freter’s nutrient niche theory, a pathogen
can only invade if it is able to use a specic limiting nutrient
more eciently than the rest of the community, which means
colonization resistance against pathogens is aected by ecient
restriction of all available nutrient niches by a complex
microbial community (Freter etal., 1983). Invasion theory
Figures out that biotic selection could be the critical
determinant (Dillon etal., 2005; van Elsas etal., 2012; Mallon
etal., 2015; Ketola etal., 2017). Higher diversity communities
can competitively exclude an invader by reducing the
availability of ecological niches and eciently utilizing
resources (Hromada etal., 2021). us, the protective eect is
probably provided through antagonism between microbes
(Chiu etal., 2017; Ubeda etal., 2017). In the case of an animal
pathogen, three facultative anaerobes potentially prevent
infection in Oligo-MM
mice by lling up the niche space that
is preferred by S. Tm (Brugiroux etal., 2016). Previous studies
showed that H. alvei reduced nitrates and fermented
l-arabinose, glycerol, maltose, d-mannitol, d-mannose,
l-rhamnose, trehalose, and d-xylose (Møller, 1954; Janda etal.,
2005; Tian and Moran, 2016; Erban etal., 2017). Genomic
analysis reveals that H. alvei harbors various carbohydrate
degradation modules and has similar functions as the Core-20
(Figure4), suggesting its ability to grow in the honeybee gut
and compete for multiple carbohydrates. Gilliamella, a primary
polysaccharide degrader in the honeybee gut, utilizes mannose,
arabinose, xylose, or rhamnose (monosaccharides that can
cause toxicity in bees; Zheng et al., 2016, 2017, 2019).
Functions for carbohydrate use and PTS systems are
represented in genomic analysis of the Core-20 community,
which may also promote colonization resistance by competition
for limited nutrients that H. alvei presumably depends on. Our
ndings implied that protection by the Gilliamella and the
Core-20 bees occurs via occupation of niche space (for
example, consumption of carbohydrates) that can no longer
be exploited by H. alvei. Loss of microbial diversity might
create ecological niches that pathogens can use, underlying
why bees colonized with low-complexity gut microbiota, such
as the Core-6, are more susceptible to H. alvei infection.
Whereas, because the Core-20 had 14 strains more than the
Core-6, it is conceivable that the Core-20 community could
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 12
actually ll up the niche space that is preferred by H. alvei and
thereby prevent infection.
e honey bee gut microbiota is dominated by limited
numbers of bacterial phylotypes, commonly with species from
the Gilliamella, Snodgrassella, Lactobacillus Firm-5,
Bombilactobacillus Firm-4, Bidobacterium, and Bartonella
genera. Gut microbial communities inuence host health in
many ways, including food digestion, defense against
pathogens, and modulation of behavior, development, and
immunity (Engel and Moran, 2013a,b). erefore, dysbiosis
(microbial imbalance) may impact honeybee health and
susceptibility to disease. Honeybees treated with tetracycline
severely altered both the size and composition of the gut
microbiome, decreasing the survival rate of bees and increasing
susceptibility to opportunistic pathogens (Raymann et al.,
2017; Lang etal., 2022). Here, the Core-20 consisted of typical
isolates representing species in honeybee gut microbiota,
which demonstrated transmission stability and functional
redundancy during passages. Potentially, consequences of
dysbiosis, such as nutritional impacts or heightened
susceptibility to toxins, could be reduced through the
development of alternative treatment methods, for example,
adding the Core-20 to the bee hive.
In conclusion, wehave assembled a minimal community of
20 bacterial strains that provided colonization resistance against
H. alvei, elucidating the underlying molecular and functional
mechanisms. e native gut symbionts are essential in the
resistance to pathogen invasion. Such strain collections can
yield insights into host-microbiota interactions, hoping to oer
solutions to protect honeybees from pathogen infection.
Data availability statement
e datasets presented in this study can befound in online
repositories. e names of the repository/repositories and
accession number(s) can be found in the article/
Supplementary material.
Author contributions
JW and HZ designed the research. JW, HL, and WZ
collected the samples. JW, HL, and WZ performed the
experiments and analyzed the data with contributions from
YZ, LZ, HL, and YL. JW and HZ wrote the manuscript. All
authors contributed to the article and approved the
submitted version.
is work was supported by the National Key R&D Program
of China (grant no. 2019YFA0906500).
We thank Jun Guo, Zijing Zhang, and Xiaohuan Mu for their
assistance in sample collection.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their aliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
Supplementary material
e Supplementary material for this article can befound online
qPCR primer sequences for gene expression and bacterial load.
Dierences of the V3–V4 region of 16S rRNA genes of strains in the
relevant genus. Our results indicated the feasibility of using 16S rRNA
genes V3–4 region for species classification.
Brochet, S., Quinn, A., Mars, R. A., Neuschwander, N., Sauer, U., and Engel, P.
(2021). Niche partitioning facilitates coexistence of closely related honey bee gut
bacteria. elife 10:e68583. doi: 10.7554/eLife.68583
Brugiroux, S., Beutler, M., Pfann, C., Garzetti, D., Ruscheweyh, H.-J., Ring, D.,
et al. (2016). Genome-guided design of a dened mouse microbiota that confers
colonization resistance against Salmonella enterica serovar Typhimurium. Nat.
Microbiol. 2, 1–12. doi: 10.1038/nmicrobiol.2016.215
Bue, C. G., Bucci, V., Stein, R. R., McKenney, P. T., Ling, L., Gobourne, A., et al.
(2015). Precision microbiome restoration of bile acid-mediated resistance to
Clostridium dicile. Nature 517, 205–208. doi: 10.1038/nature13828
Butler, È., Alsterord, M., Olofsson, T. C., Karlsson, C., Malmström, J., and
Vásquez, A. (2013). Proteins of novel lactic acid bacteria from Apis mellifera
mellifera: an insight into the production of known extra-cellular proteins during
microbial stress. BMC Microbiol. 13:235. doi: 10.1186/1471-2180-13-235
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 13
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C. A.,
Turnbaugh, P. J., et al. (2011). Global patterns of 16S rRNA diversity at a depth of
millions of sequences per sample. Proc. Natl. Acad. Sci. 108, 4516–4522. doi:
Chiu, L., Bazin, T., Truchetet, M.-E., Schaeverbeke, T., Delhaes, L., and Pradeu, T.
(2017). Protective microbiota: from localized to long-reaching co-immunity. Front.
Immunol. 8:1678. doi: 10.3389/mmu.2017.01678
Daisley, B. A., Pitek, A. P., Chmiel, J. A., Al, K. F., Chernyshova, A. M.,
Faragalla, K. M., et al. (2020a). Novel probiotic approach to counter Paenibacillus
larvae infection in honey bees. ISME J. 14, 476–491. doi: 10.1038/s41396-019-0541-6
Daisley, B. A., Pitek, A. P., Chmiel, J. A., Gibbons, S., Chernyshova, A. M., Al, K. F.,
et al. (2020b). Lactobacillus spp. attenuate antibiotic-induced immune and
microbiota dysregulation in honey bees. Commun. Biol. 3, 1–13. doi: 10.1038/
Danihlík, J., Aronstein, K., and Petřivalský, M. (2015). Antimicrobial peptides: a
key component of honey bee innate immunity. J. Apic. Res. 54, 123–136. doi:
Diep, D. B., Skaugen, M., Salehian, Z., Holo, H., and Nes, I. F. (2007). Common
mechanisms of target cell recognition and immunity for class II bacteriocins. Proc.
Natl. Acad. Sci. U. S. A. 104, 2384–2389. doi: 10.1073/pnas.0608775104
Dillon, R. J., Vennard, C. T., Buckling, A., and Charnley, A. K. (2005). Diversity
of locust gut bacteria protects against pathogen invasion. Ecol. Lett. 8, 1291–1298.
doi: 10.1111/j.1461-0248.2005.00828.x
Ellegaard, K. M., Brochet, S., Bonilla-Rosso, G., Emery, O., Glover, N., Hadadi, N.,
et al. (2019). Genomic changes underlying host specialization in the bee gut
symbiont Lactobacillus Firm5. Mol. Ecol. 28, 2224–2237. doi: 10.1111/mec.15075
Emery, O., Schmidt, K., and Engel, P. (2017). Immune system stimulation by the
gut symbiont Frischella perrara in the honey bee (Apis mellifera). Mol. Ecol. 26,
2576–2590. doi: 10.1111/mec.14058
Engel, P., Kwong, W. K., McFrederick, Q., Anderson, K. E., Barribeau, S. M.,
Chandler, J. A., et al. (2016). e bee microbiome: impact on bee health and model
for evolution and ecology of host-microbe interactions. MBio 7, e02164–e02115.
doi: 10.1128/mBio.02164-15
Engel, P., and Moran, N. A. (2013a). Functional and evolutionary insights into the
simple yet specic gut microbiota of the honey bee from metagenomic analysis. Gut
Microbes 4, 60–65. doi: 10.4161/gmic.22517
Engel, P., and Moran, N. A. (2013b). e gut microbiota of insects – diversity in
structure and function. FEMS Microbiol. Rev. 37, 699–735. doi: 10.1111/1574-
Erban, T., Ledvinka, O., Kamler, M., Nesvorna, M., Hortova, B., Tyl, J., et al.
(2017). Honeybee (Apis mellifera)-associated bacterial community aected by
American foulbrood: detection of Paenibacillus larvae via microbiome analysis. Sci.
Rep. 7, 1–10. doi: 10.1038/s41598-017-05076-8
Evans, J. D., Aronstein, K., Chen, Y. P., Hetru, C., Imler, J.-L., Jiang, H., et al.
(2006). Immune pathways and defence mechanisms in honey bees Apis mellifera.
Insect Mol. Biol. 15, 645–656. doi: 10.1111/j.1365-2583.2006.00682.x
Fan, T.-J., Goeser, L., Naziripour, A., Redinbo, M. R., and Hansen, J. J. (2019).
Enterococcus faecalis gluconate phosphotransferase system accelerates experimental
colitis and bacterial killing by macrophages. Infect. Immun. 87, e00080–e00019. doi:
Forsgren, E., Olofsson, T. C., Vásquez, A., and Fries, I. (2010). Novel lactic acid
bacteria inhibiting Paenibacillus larvae in honey bee larvae. Apidologie 41, 99–108.
doi: 10.1051/apido/2009065
Freter, R., Brickner, H., Botney, M., Cleven, D., and Aranki, A. (1983). Mechanisms
that control bacterial populations in continuous-ow culture models of mouse large
intestinal ora. Infect . Immun. 39, 676–685. doi: 10.1128/iai.39.2.676-685.1983
Fünaus, A., Ebeling, J., and Genersch, E. (2018). Bacterial pathogens of bees.
Curr. Opin. Insect Sci. 26, 89–96. doi: 10.1016/j.cois.2018.02.008
Gabor, E., Göhler, A.-K., Kosfeld, A., Staab, A., Kremling, A., and Jahreis, K.
(2011). e phosphoenolpyruvate-dependent glucose–phosphotransferase system
from Escherichia coli K-12 as the center of a network regulating carbohydrate ux
in the cell. Eur. J. Cell Biol. 90, 711–720. doi: 10.1016/j.ejcb.2011.04.002
Ghimire, S., Roy, C., Wongkuna, S., Antony, L., Maji, A., Keena, M. C., et al.
(2020). Identication of Clostridioides dicile-inhibiting gut commensals using
culturomics, phenotyping, and combinatorial community assembly. mSystems 5,
e00620–e00619. doi: 10.1128/mSystems.00620-19
Grabowski, N. T., and Klein, G. (2017). Microbiology and foodborne pathogens
in honey. Crit. Rev. Food Sci. Nutr. 57, 1852–1862. doi: 10.1080/10408398.2015.
Guo, Y., Zhang, Z., Zhuang, M., Wang, L., Li, K., Yao, J., et al. (2021).
Transcriptome proling reveals a novel mechanism of antiviral immunity upon
sacbrood virus infection in honey bee larvae (Apis cerana). Front. Microbiol.
12:615893. doi: 10.3389/fmicb.2021.615893
Horak, R. D., Leonard, S. P., and Moran, N. A. (2020). Symbionts shape host
innate immunity in honeybees. Proc. R. Soc. B Biol. Sci. 287:20201184. doi: 10.1098/
Houot, L., Chang, S., Absalon, C., and Watnick, P. I. (2010). Vibrio cholerae
phosphoenolpyruvate phosphotransferase system control of carbohydrate transport,
biolm formation, and colonization of the germfree mouse intestine. Infect . Immun.
78, 1482–1494. doi: 10.1128/IAI.01356-09
Hromada, S., Qian, Y., Jacobson, T. B., Clark, R. L., Watson, L., Safdar, N., et al.
(2021). Negative interactions determine Clostridioides difficile growth in
synthetic human gut communities. Mol. Syst. Biol. 17:e10355. doi: 10.15252/
Janda, J. M., Abbott, S. L., Bystrom, S., and Probert, W. S. (2005). Identication of
two distinct hybridization groups in the genus Hafnia by 16S rRNA gene sequencing
and phenotypic methods. J. Clin. Microbiol. 43, 3320–3323. doi: 10.1128/
Kamada, N., Chen, G. Y., Inohara, N., and Núñez, G. (2013). Control of pathogens
and pathobionts by the gut microbiota. Nat. Immunol. 14, 685–690. doi: 10.1038/
Kanehisa, M., Sato, Y., and Kawashima, M. (2022). KEGG mapping tools for
uncovering hidden features in biological data. Protein Sci. 31, 47–53. doi: 10.1002/
Kešnerová, L., Emery, O., Troilo, M., Liberti, J., Erkosar, B., and Engel, P. (2020).
Gut microbiota structure diers between honeybees in winter and summer. ISME
J. 14, 801–814. doi: 10.1038/s41396-019-0568-8
Ketola, T., Saarinen, K., and Lindström, L. (2017). Propagule pressure increase
and phylogenetic diversity decrease community’s susceptibility to invasion. BMC
Ecol. 17:15. doi: 10.1186/s12898-017-0126-z
Killer, J., Dubná, S., Sedláček, I., and Švec, P. (2014). Lac tobacillus apis sp. nov.,
from the stomach of honeybees (Apis mellifera), having an in vitro inhibitory eect
on the causative agents of American and European foulbrood. Int. J. Syst. Evol.
Microbiol. 64, 152–157. doi: 10.1099/ijs.0.053033-0
Kim, S., Covington, A., and Pamer, E. G. (2017). e intestinal microbiota:
antibiotics, colonization resistance, and enteric pathogens. Immunol. Rev. 279,
90–105. doi: 10.1111/imr.12563
Kjos, M., Salehian, Z., Nes, I. F., and Diep, D. B. (2010). An extracellular loop of
the mannose phosphotransferase system component IIC is responsible for specic
targeting by class IIa bacteriocins. J. Bacteriol. 192, 5906–5913. doi: 10.1128/
Koch, H., Abrol, D. P., Li, J., and Schmid-Hempel, P. (2013). Diversity and
evolutionary patterns of bacterial gut associates of corbiculate bees. Mol. Ecol. 22,
2028–2044. doi: 10.1111/mec.12209
Kotrba, P., Inui, M., and Yukawa, H. (2001). Bacterial phosphotransferase system
(PTS) in carbohydrate uptake and control of carbon metabolism. J. Biosci. Bioeng.
92, 502–517. doi: 10.1016/S1389-1723(01)80308-X
Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K., and Schloss, P. D.
(2013). Development of a dual-index sequencing strategy and curation pipeline for
analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.
Appl. Environ. Microbiol. 79, 5112–5120. doi: 10.1128/AEM.01043-13
Kwong, W. K., Mancenido, A. L., and Moran, N. A. (2017). Immune system
stimulation by the native gut microbiota of honey bees. R. Soc. Open Sci. 4:170003.
doi: 10.1098/rsos.170003
Kwong, W. K., and Moran, N. A. (2016). Gut microbial communities of social
bees. Nat. Rev. Microbiol. 14, 374–384. doi: 10.1038/nrmicro.2016.43
Lang, H., Duan, H., Wang, J., Zhang, W., Guo, J., Zhang, X., et al. (2022). Specic
strains of honeybee gut Lactobacillus stimulate host immune system to protect
against pathogenic Hafnia alvei. Microbiol. Spectr. 10:e0189621. doi: 10.1128/
Lawley, T. D., and Walker, A. W. (2013). Intestinal colonization resistance.
Immunology 138, 1–11. doi: 10.1111/j.1365-2567.2012.03616.x
Lee, F. J., Rusch, D. B., Stewart, F. J., Mattila, H. R., and Newton, I. L. G. (2015).
Saccharide breakdown and fermentation by t he honey bee gut microbiome. Environ.
Microbiol. 17, 796–815. doi: 10.1111/1462-2920.12526
Liu, Y., Chen, J., Lang, H., and Zheng, H. (2022). Bartonella choladocola sp. nov.
and Bartonella apihabitans sp. nov., two novel species isolated from honey bee gut.
Syst. Appl. Microbiol. 45:126372. doi: 10.1016/j.syapm.2022.126372
Lourenço, A. P., Florecki, M. M., Simões, Z. L. P., and Evans, J. D. (2018).
Silencing of Apis mellifera dorsal genes reveals their role in expression of the
antimicrobial peptide defensin-1. Insect Mol. Biol. 27, 577–589. doi: 10.1111/
Lourenço, A. P., Guidugli-Lazzarini, K. R., Freitas, F. C. P., Bitondi, M. M. G., and
Simões, Z. L. P. (2013). Bacterial infection activates the immune system response
and dysregulates microRNA expression in honey bees. Insect Biochem. Mol. Biol. 43,
474–482. doi: 10.1016/j.ibmb.2013.03.001
Wang et al. 10.3389/fmicb.2022.1074153
Frontiers in Microbiology 14
Mallon, C. A., van Elsas, J. D., and Salles, J. F. (2015). Microbial invasions: the
process, patterns, and mechanisms. Trends Microbiol. 23, 719–729. doi: 10.1016/j.
Martinson, V. G., Danforth, B. N., Minckley, R. L., Rueppell, O., Tingek, S., and
Moran, N. A. (2011). A simple and distinctive microbiota associated with honey
bees and bumble bees. Mol. Ecol. 20, 619–628. doi: 10.1111/j.1365-294X.2010.04959.x
Martinson, V. G., Moy, J., and Moran, N. A. (2012). Establishment of characteristic
gut bacteria during development of the honeybee worker. Appl. Environ. Microbiol.
78, 2830–2840. doi: 10.1128/AEM.07810-11
Møller, V. (1954). Distribution of amino acid decarboxylases in Enterobacteriaceae1.
Acta Pathol. Microbiol. Scand. 35, 259–277. doi: 10.1111/j.1699-0463.1954.tb00869.x
Moriya, Y., Itoh, M., Okuda, S., Yoshizawa, A. C., and Kanehisa, M. (2007). KAAS:
an automatic genome annotation and pathway reconstruction server. Nucleic Acids
Res. 35, 182–185. doi: 10.1093/nar/gkm321
Pereira, F. C., and Berr y, D. (2017). Microbial nutrient niches in the gut. Environ.
Microbiol. 19, 1366–1378. doi: 10.1111/1462-2920.13659
Powell, J. E., Mar tinson, V. G., Urban-Mead, K., and Moran, N. A. (2014). Routes
of acquisition of the gut microbiota of the honey bee Apis mellifera. Appl. Environ.
Microbiol. 80, 7378–7387. doi: 10.1128/AEM.01861-14
Raymann, K., and Moran, N. A. (2018). e role of the gut microbiome in health
and disease of adult honey bee workers. Curr. Opin. Insect Sci. 26, 97–104. doi:
Raymann, K., Shaer, Z., and Moran, N. A. (2017). Antibiotic exposure perturbs
the gut microbiota and elevates mortality in honeybees. PLoS Biol. 15:e2001861. doi:
Schloss, P. D. (2020). Reintroducing mothur: 10 years later. Appl. Environ.
Microbiol. 86, e02343–e02319. doi: 10.1128/AEM.02343-19
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B.,
et al. (2009). Introducing mothur: open-source, platform-independent, community-
supported soware for describing and comparing microbial communities. Appl.
Environ. Microbiol. 75, 7537–7541. doi: 10.1128/AEM.01541-09
Spees, A. M., Lopez, C. A., Kingsbury, D. D., Winter, S. E., and Bäumler, A. J.
(2013). Colonization resistance: battle of the bugs or ménage à trois with the host?
PLoS Pathog. 9:e1003730. doi: 10.1371/journal.ppat.1003730
Steele, M. I., Kwong, W. K., Whiteley, M., and Moran, N. A. (2017). Diversication
of type VI secretion system toxins reveals ancient antagonism among bee gut
microbes. mBio 8, e01630–e01617. doi: 10.1128/mBio.01630-17
Su, Q., Wang, Q., Mu, X., Chen, H., Meng, Y., Zhang, X., et al. (2021). Strain-level
analysis reveals the vertical microbial transmission during the life cycle of
bumblebee. Microbiome 9:216. doi: 10.1186/s40168-021-01163-1
Tian, B., and Moran, N. A. (2016). Genome sequence of Hafnia alvei bta3_1, a
bacterium with antimicrobial properties isolated from honey bee gut. Genome
Announc. 4, e00439–e00416. doi: 10.1128/genomeA.00439-16
Ubeda, C., Djukovic, A., and Isaac, S. (2017). Roles of the intestinal microbiota in
pathogen protection. Clin. Transl. Immunol. 6:128. doi: 10.1038/cti.2017.2
van Elsas, J. D., Chiurazzi, M., Mallon, C. A., Elhottova, D., Kristufek, V., and
Salles, J. F. (2012). Microbial diversity determines the invasion of soil by a bacterial
pathogen. Proc. Natl. Acad. Sci. U. S. A. 109, 1159–1164. doi: 10.1073/
Vásquez, A., Forsgren, E., Fries, I., Paxton, R. J., Flaberg, E., Szekely, L., et al.
(2012). Symbionts as major modulators of insect health: lactic acid bacteria and
honeybees. PLoS One 7:e33188. doi: 10.1371/annotation/3ac2b867-c013-4504-9e06-
Wu, J., Lang, H., Mu, X., Zhang, Z., Su, Q., Hu, X., et al. (2021). Honey bee genetics
shape the strain-level structure of gut microbiota in social transmission. Microbiome
9:225. doi: 10.1186/s40168-021-01174-y
Xu, L., Dong, Z., Fang, L., Luo, Y., Wei, Z., Guo, H., et al. (2019). OrthoVenn2: a
web server for whole-genome comparison and annotation of orthologous clusters
across multiple species. Nucleic Acids Res. 47, 52–58. doi: 10.1093/nar/gkz333
Xue, Z., Xingan, L., Qinzhi, S., Qina, C., Chenyi, L., Qingsheng, N., et al. (2019).
A curated 16S rRNA reference database for the classication of honeybee and
bumblebee gut microbiota. Biodivers. Sci. 27:557. doi: 10.17520/biods.2019021
Yoo, J. Y., Groer, M., Dutra, S. V. O., Sarkar, A., and McSkimming, D. I. (2020).
Gut microbiota and immune system interactions. Microorganisms 8:1587. doi:
Zheng, H., Nishida, A., Kwong, W. K., Koch, H., Engel, P., Steele, M. I., et al.
(2016). Metabolism of toxic sugars by strains of the bee gut symbiont Gilliamella
apicola. mBio 7, e01326–e01316. doi: 10.1128/mBio.01326-16
Zheng, H., Perreau, J., Powell, J. E., Han, B., Zhang, Z., Kwong, W. K., et al. (2019).
Division of labor in honey bee gut microbiota for plant polysaccharide digestion.
Proc. Natl. Acad. Sci. 116, 25909–25916. doi: 10.1073/pnas.1916224116
Zheng, H., Powell, J. E., Steele, M. I., Dietrich, C., and Moran, N. A. (2017). Honeybee
gut microbiota promotes host weight gain via bacterial metabolism and hormonal
signaling. Proc. Natl. Acad. Sci. 114, 4775–4780. doi: 10.1073/pnas.1701819114
Zheng, H., Steele, M. I., Leonard, S. P., Motta, E. V. S., and Moran, N. A. (2018).
Honey bees as models for gut microbiota research. Lab. Anim. 47, 317–325. doi:
Zhou, W., Wang, G., Wang, C., Ren, F., and Hao, Y. (2016). Both IIC and IID
components of mannose phosphotransferase system are involved in the specic
recognition between immunity protein PedB and bacteriocin-receptor complex.
PLoS One 11:e0164973. doi: 10.1371/journal.pone.0164973
ResearchGate has not been able to resolve any citations for this publication.
Full-text available
Honeybees are essential pollinators supporting global agricultural economies and food supplies. Recent honeybee decline has been linked to several factors, while pathogen infection is considered one of the most significant contributing factors.
Full-text available
Background Honey bee gut microbiota transmitted via social interactions are beneficial to the host health. Although the microbial community is relatively stable, individual variations and high strain-level diversity have been detected across honey bees. Although the bee gut microbiota structure is influenced by environmental factors, the heritability of the gut members and the contribution of the host genetics remains elusive. Considering bees within a colony are not readily genetically identical due to the polyandry of the queen, we hypothesize that the microbiota structure can be shaped by host genetics. Results We used shotgun metagenomics to simultaneously profile the microbiota and host genotypes of bees from hives of four different subspecies. Gut composition is more distant between genetically different bees at both phylotype- and “sequence-discrete population” levels. We then performed a successive passaging experiment within colonies of hybrid bees generated by artificial insemination, which revealed that the microbial composition dramatically shifts across batches of bees during the social transmission. Specifically, different strains from the phylotype of Snodgrassella alvi are preferentially selected by genetically varied hosts, and strains from different hosts show a remarkably biased distribution of single-nucleotide polymorphism in the Type IV pili loci. Genome-wide association analysis identified that the relative abundance of a cluster of Bifidobacterium strains is associated with the host glutamate receptor gene specifically expressed in the bee brain. Finally, mono-colonization of Bifidobacterium with a specific polysaccharide utilization locus impacts the alternative splicing of the gluR-B gene, which is associated with an increased GABA level in the brain. Conclusions Our results indicated that host genetics influence the bee gut composition and suggest a gut-brain connection implicated in the gut bacterial strain preference. Honey bees have been used extensively as a model organism for social behaviors, genetics, and the gut microbiome. Further identification of host genetic function as a shaping force of microbial structure will advance our understanding of the host-microbe interactions. 45gpjtUuBYRAxeW78Mk2MGVideo abstract
Full-text available
Background Microbial acquisition and development of the gut microbiota impact the establishment of a healthy host-microbes symbiosis. Compared with other animals, the eusocial bumblebees and honeybees possess a simple, recurring, and similar set of gut microbiota. However, all bee gut phylotypes have high strain-level diversity. Gut communities of different bee species are composed of host-specific groups of strains. The variable genomic regions among strains of the same species often confer critical functional differences, such as carbon source utilization, essential for the natural selection of specific strains. The annual bumblebee colony founded by solitary queens enables tracking the transmission routes of gut bacteria during development stages. Results Here, we first showed the changes in the microbiome of individual bumblebees across their holometabolous life cycle. Some core gut bacteria persist throughout different stages of development. Gut microbiota of newly emerged workers always resembles those of their queens, suggesting a vertical transmission of strains from queens to the newborn workers. We then follow the dynamic changes in the gut community by comparing strain-level metagenomic profiles of queen-worker pairs longitudinally collected across different stages of the nest development. Species composition of both queen and worker shifts with the colony’s growth, and the queen-to-worker vertical inheritance of specific strains was identified. Finally, comparative metagenome analysis showed clear host-specificity for microbes across different bee hosts. Species from honeybees often possess a higher level of strain variation, and they also exhibited more complex gene repertoires linked to polysaccharide digestion. Our results demonstrate bacterial transmission events in bumblebee, highlighting the role of social interactions in driving the microbiota composition. Conclusions By the community-wide metagenomic analysis based on the custom genomic database of bee gut bacteria, we reveal strain transmission events at high resolution and the dynamic changes in community structure along with the colony development. The social annual life cycle of bumblebees is key for the acquisition and development of the gut microbiota. Further studies using the bumblebee model will advance our understanding of the microbiome transmission and the underlying mechanisms, such as strain competition and niche selection.
Full-text available
Understanding the principles of colonization resistance of the gut microbiome to the pathogen Clostridioides difficile will enable the design of defined bacterial therapeutics. We investigate the ecological principles of community resistance to C. difficile using a synthetic human gut microbiome. Using a dynamic computational model, we demonstrate that C. difficile receives the largest number and magnitude of incoming negative interactions. Our results show that C. difficile is in a unique class of species that display a strong negative dependence between growth and species richness. We identify molecular mechanisms of inhibition including acidification of the environment and competition over resources. We demonstrate that Clostridium hiranonis strongly inhibits C. difficile partially via resource competition. Increasing the initial density of C. difficile can increase its abundance in the assembled community, but community context determines the maximum achievable C. difficile abundance. Our work suggests that the C. difficile inhibitory potential of defined bacterial therapeutics can be optimized by designing communities featuring a combination of mechanisms including species richness, environment acidification, and resource competition.
Full-text available
Ecological processes underlying bacterial coexistence in the gut are not well understood. Here, we disentangled the effect of the host and the diet on the coexistence of four closely related Lactobacillus species colonizing the honey bee gut. We serially passaged the four species through gnotobiotic bees and in liquid cultures in the presence of either pollen (bee diet) or simple sugars. Although the four species engaged in negative interactions, they were able to stably coexist, both in vivo and in vitro . However, coexistence was only possible in the presence of pollen, and not in simple sugars, independent of the environment. Using metatranscriptomics and metabolomics, we found that the four species utilize different pollen-derived carbohydrate substrates indicating resource partitioning as the basis of coexistence. Our results show that despite longstanding host association, gut bacterial interactions can be recapitulated in vitro providing insights about bacterial coexistence when combined with in vivo experiments.
Full-text available
The honey bee is one of the most important pollinators in the agricultural system and is responsible for pollinating a third of all food we eat. Sacbrood virus (SBV) is a member of the virus family Iflaviridae and affects honey bee larvae and causes particularly devastating disease in the Asian honey bees, Apis cerana . Chinese Sacbrood virus (CSBV) is a geographic strain of SBV identified in China and has resulted in mass death of honey bees in China in recent years. However, the molecular mechanism underlying SBV infection in the Asian honey bee has remained unelucidated. In this present study, we employed high throughput next-generation sequencing technology to study the host transcriptional responses to CSBV infection in A. cerana larvae, and were able to identify genome-wide differentially expressed genes associated with the viral infection. Our study identified 2,534 differentially expressed genes (DEGs) involved in host innate immunity including Toll and immune deficiency (IMD) pathways, RNA interference (RNAi) pathway, endocytosis, etc. Notably, the expression of genes encoding antimicrobial peptides ( abaecin , apidaecin , hymenoptaecin , and defensin ) and core components of RNAi such as Dicer-like and Ago2 were found to be significantly upregulated in CSBV infected larvae. Most importantly, the expression of Sirtuin target genes, a family of signaling proteins involved in metabolic regulation, apoptosis, and intracellular signaling was found to be changed, providing the first evidence of the involvement of Sirtuin signaling pathway in insects’ immune response to a virus infection. The results obtained from this study provide novel insights into the molecular mechanism and immune responses involved in CSBV infection, which in turn will contribute to the development of diagnostics and treatment for the diseases in honey bees.
Full-text available
Dynamic interactions between gut microbiota and a host’s innate and adaptive immune systems play key roles in maintaining intestinal homeostasis and inhibiting inflammation. The gut microbiota metabolizes proteins and complex carbohydrates, synthesize vitamins, and produce an enormous number of metabolic products that can mediate cross-talk between gut epithelial and immune cells. As a defense mechanism, gut epithelial cells produce a mucosal barrier to segregate microbiota from host immune cells and reduce intestinal permeability. An impaired interaction between gut microbiota and the mucosal immune system can lead to an increased abundance of potentially pathogenic gram-negative bacteria and their associated metabolic changes, disrupting the epithelial barrier and increasing susceptibility to infections. Gut dysbiosis, or negative alterations in gut microbial composition, can also dysregulate immune responses, causing inflammation, oxidative stress, and insulin resistance. Over time, chronic dysbiosis and the translocation of bacteria and their metabolic products across the mucosal barrier may increase prevalence of type 2 diabetes, cardiovascular disease, inflammatory bowel disease, autoimmune disease, and a variety of cancers. In this paper, we highlight the pivotal role gut microbiota and their metabolites (short-chain fatty acids (SCFAs)) play in mucosal immunity.
Full-text available
Widespread antibiotic usage in apiculture contributes substantially to the global dissemination of antimicrobial resistance and has the potential to negatively influence bacterial symbionts of honey bees (Apis mellifera). Here, we show that routine antibiotic administration with oxytetracycline selectively increased tetB (efflux pump resistance gene) abundance in the gut microbiota of adult workers while concurrently depleting several key symbionts known to regulate immune function and nutrient metabolism such as Frischella perrera and Lactobacillus Firm-5 strains. These microbial changes were functionally characterized by decreased capped brood counts (marker of hive nutritional status and productivity) and reduced antimicrobial capacity of adult hemolymph (indicator of immune competence). Importantly, combination therapy with three immunostimulatory Lactobacillus strains could mitigate antibiotic-associated microbiota dysbiosis and immune deficits in adult workers, as well as maximize the intended benefit of oxytetracycline by suppressing larval pathogen loads to near-undetectable levels. We conclude that microbial-based therapeutics may offer a simple but effective solution to reduce honey bee disease burden, environmental xenobiotic exposure, and spread of antimicrobial resistance.
Bartonella is one of the noncore bacterial genera in the honey bee (Apis mellifera) gut. So far, only one species, Bartonella apis, has been described from the honey bee gut. Previous analyses based on the genomic information of isolates and metagenome-assembled genomes suggested the existence of multiple Bartonella species in the bee guts. Here, 10 strains were isolated and characterized from the gut of A. mellifera from Jilin Province, China. New isolates shared >95% 16S rRNA gene sequence similarity with other species of the genus Bartonella. Phylogenetic analysis revealed that new isolates clustered with other type strains of Bartonella, and the bee gut Bartonella could be classified into three clades. The in silico DDH and average nucleotide identity values between strains of different clusters from the honey bee gut are 29.1-32.5% and 87.6-89.3%, all below the recommended 70.0% and 95% cutoff points. Cells are Gram-staining-negative rods and can grow on the surface of Brain Heart Infusion agar plates supplemented with defibrinated sheep blood in an aerobic environment with 5% CO2 at 35-37 ℃. Strains from different species varied in both phenotypic and chemotaxonomic characterizations. Comparative genomic analysis indicated that B. choladocola had unique sets of genes encoding invasin, representing the potential for this species to both live as a gut symbiont and also as an erythrocytic pathogen. Thus, we propose two novel species Bartonella choladocola sp. nov. whose type strain is W8125T(=JCM 35030T =ACCC 62057T) and Bartonella apihabitans sp. nov. whose type strain is W8097T(=JCM 35029T=ACCC 62056T).
In contrast to artificial intelligence and machine learning approaches, KEGG ( has relied on human intelligence to develop “models” of biological systems, especially in the form of KEGG pathway maps that are manually created by capturing knowledge from published literature. The KEGG models can then be used in biological big data analysis, for example, for uncovering systemic functions of an organism hidden in its genome sequence through the simple procedure of KEGG mapping. Here we present an updated version of KEGG Mapper, a suite of KEGG mapping tools reported previously (Kanehisa and Sato, Protein Sci 2020; 29:28–35), together with the new versions of the KEGG pathway map viewer and the BRITE hierarchy viewer. Significant enhancements have been made for BRITE mapping, where the mapping result can be examined by manipulation of hierarchical trees, such as pruning and zooming. The tree manipulation feature has also been implemented in the taxonomy mapping tool for linking KO (KEGG Orthology) groups and modules to phenotypes. This article is protected by copyright. All rights reserved.