Back

A Meta-Analysis of the 16S-rRNA Gut Microbiome Data in Honeybees (Apis Mellifera)

Gkantiragas, A.; Gabrielli, J.

2021-12-20 ecology
10.1101/2021.12.18.473299 bioRxiv
Show abstract

1.Honeybees (Apis Mellifera) perform an essential role in the ecosystem and economy through pollination of insect-pollinated plants, but their population is declining. Many causes of honeybees decline are likely to be influenced by the microbiome which is thought to play an important role in bees and is particularly susceptible to infection and pesticides. However, there has been no systematic review or meta-analysis on honeybee microbiome data. Therefore, we conducted the first systematic meta-analysis of 16S-rRNA data to address this gap in the literature. Four studies were in a usable format - accounting for 336 honeybees worth of data - the largest such dataset to the best of our knowledge. We analysed these datasets in QIIME2 and visualised the results in R-studio. For the first time, we conducted a multi-study evaluation of the core and rare bee microbiome and confirmed previous compositional microbiome data. We established that Snodgrassella, Lactobacillus, Bifidobacterium, Fructobacillus and Saccaribacter form part of the core microbiome and identify 251 rare bacterial genera. Additional components of the core microbiome were likely obscured by incomplete classification. Future studies should refine and add to our existing dataset to produce a more conclusive and high-resolution portrait of the honeybee microbiome. Furthermore, we emphasise the need for an actively curated dataset and enforcement of data sharing standards. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/473299v1_fig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1d9c414org.highwire.dtl.DTLVardef@1d82d2forg.highwire.dtl.DTLVardef@17e6aa1org.highwire.dtl.DTLVardef@8aa415_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1C_FLOATNO Graphical abstract. Made by the author in Biorender.com. C_FIG

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
mSystems
361 papers in training set
Top 0.8%
10.0%
2
Microbial Ecology
28 papers in training set
Top 0.1%
6.7%
3
PLOS ONE
4510 papers in training set
Top 29%
6.3%
4
Scientific Reports
3102 papers in training set
Top 20%
6.2%
5
ISME Communications
103 papers in training set
Top 0.3%
4.8%
6
Microbiome
139 papers in training set
Top 0.7%
4.8%
7
Ecology and Evolution
232 papers in training set
Top 0.7%
4.3%
8
PeerJ
261 papers in training set
Top 2%
3.6%
9
Scientific Data
174 papers in training set
Top 0.5%
3.5%
50% of probability mass above
10
eLife
5422 papers in training set
Top 26%
3.5%
11
Nature Communications
4913 papers in training set
Top 42%
3.0%
12
Frontiers in Microbiology
375 papers in training set
Top 3%
2.7%
13
Molecular Ecology
304 papers in training set
Top 2%
2.3%
14
Environmental Microbiology
119 papers in training set
Top 1%
2.1%
15
mSphere
281 papers in training set
Top 3%
1.9%
16
Environmental Microbiome
26 papers in training set
Top 0.2%
1.9%
17
Frontiers in Ecology and Evolution
60 papers in training set
Top 2%
1.8%
18
Molecular Ecology Resources
161 papers in training set
Top 0.6%
1.7%
19
Science of The Total Environment
179 papers in training set
Top 3%
1.5%
20
Methods in Ecology and Evolution
160 papers in training set
Top 2%
1.5%
21
PLOS Biology
408 papers in training set
Top 13%
1.3%
22
Microorganisms
101 papers in training set
Top 1%
1.3%
23
iScience
1063 papers in training set
Top 23%
1.1%
24
PLOS Computational Biology
1633 papers in training set
Top 22%
0.9%
25
BMC Biology
248 papers in training set
Top 3%
0.9%
26
npj Biofilms and Microbiomes
56 papers in training set
Top 2%
0.9%
27
Environmental DNA
49 papers in training set
Top 0.3%
0.8%
28
GigaScience
172 papers in training set
Top 3%
0.8%
29
Communications Biology
886 papers in training set
Top 22%
0.8%
30
Peer Community Journal
254 papers in training set
Top 4%
0.7%