Evidence map›Paper›PMID 36674732›Full record

ArticleInternational journal of molecular sciences2023

ame-miR-34 Modulates the Larval Body Weight and Immune Response of

Ying Wu, Yilong Guo, Xiaoxue Fan, Haodong Zhao, Yiqiong Zhang, Sijia Guo, Xin Jing, Zhitan Liu, Peilin Feng, Xiaoyu Liu and 6 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. lncRNA1386.1/novel-miR0032-5p Axis TargetsAntioxidants (Basel, Switzerland) · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. ame-miR-5119-Frontiers in physiology · 2024
    Article
  8. Article
  9. First Characterization and Regulatory Function of piRNAs in theInternational journal of molecular sciences · 2023
    Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Ying WuCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Yilong GuoCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xiaoxue FanCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Haodong ZhaoCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Yiqiong ZhangCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Sijia GuoCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xin JingCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Zhitan LiuCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Peilin FengCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xiaoyu LiuCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Peiyuan ZouCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Qiming LiCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Zhihao NaCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Kuihao ZhangCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Dafu ChenCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Rui GuoCollege of Animal Sciences (College of Bee Science), Fujian Agriculture and Forestry University, Fuzhou 350002, China.

Funding

Earmarked fund for China Agriculture Research System CARS-44-KXJ7Master Supervisor Team Fund of Fujian Agriculture and Forestry University Rui GuoNational Natural Science Foundation of China 31702190Scientific Research Project of College of Animal Sciences (College of Bee Science) of Fujian Ag-riculture and Forestry University Rui GuoUndergraduate Innovation and Entrepreneurship Training Program of Fujian province 202210389131Undergraduate Innovation and Entrepreneurship Training Program of Fujian province S202110389070Undergraduate Innovation and Entrepreneurship Training Program of Fujian province S202110389073
6 · The paper itself

Abstract

MiRNAs are critical regulators of numerous physiological and pathological processes. Ascosphaera apis exclusively infects bee larvae and causes chalkbrood disease. However, the function and mechanism of miRNAs in the bee larval response to A. apis infection is poorly understood. Here, ame-miR-34, a previously predicted miRNA involved in the response of Apis mellifera larvae to A. apis invasion, was subjected to molecular validation, and overexpression and knockdown were then conducted to explore the regulatory functions of ame-miR-34 in larval body weight and immune response. Stem-loop RT-PCR and Sanger sequencing confirmed the authenticity of ame-miR-34 in the larval gut of A. mellifera. RT-qPCR results demonstrated that compared with that in the uninfected larval guts, the expression level of ame-miR-34 was significantly downregulated (p < 0.001) in the guts of A. apis-infected 4-, 5-, and 6-day-old larvae, indicative of the remarkable suppression of host ame-miR-34 due to A. apis infection. In comparison with the corresponding negative control (NC) groups, the expression level of ame-miR-34 in the larval guts in the mimic-miR-34 group was significantly upregulated (p < 0.001), while that in the inhibitor-miR-34 group was significantly downregulated (p < 0.01). Similarly, effective overexpression and knockdown of ame-miR-34 were achieved. In addition, the body weights of 5- and 6-day-old larvae were significantly increased compared with those in the mimic-NC group; the weights of 5-day-old larvae in the inhibitor-miR-34 group were significantly decreased in comparison with those in the inhibitor-NC group, while the weights of 4- and 6-day-old larvae in the inhibitor-miR-34 group were significantly increased, indicating the involvement of ame-miR-34 in modulating larval body weight. Furthermore, the expression levels of both hsp and abct in the guts of A. apis-infected 4-, 5-, and 6-day-old larvae were significantly upregulated after ame-miR-34 overexpression. In contrast, after ame-miR-34 knockdown, the expression levels of the aforementioned two key genes in the A. apis-infected 4-, 5-, and 6-day-old larval guts were significantly downregulated. Together, the results demonstrated that effective overexpression and knockdown of ame-miR-34 in both noninfected and A. apis-infected A. mellifera larval guts could be achieved by the feeding method, and ame-miR-34 exerted a regulatory function in the host immune response to A. apis invasion through positive regulation of the expression of hsp and abct. Our findings not only provide a valuable reference for the functional investigation of bee larval miRNAs but also reveal the regulatory role of ame-miR-34 in A. mellifera larval weight and immune response. Additionally, the results of this study may provide a promising molecular target for the treatment of chalkbrood disease.

Indexed as

ArthrodermataceaeBeesMicroRNAsAnimalsBody WeightImmunityLarvaMicroRNAsApis melliferaAscosphaera apisbody weighthoney beeimmune responselarvamiR-34

Identifiers

PMID36674732
PMCPMC9863880

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.