Evidence map›Paper›PMID 41428602›Full record

ArticleMicrobial biotechnology2025

Enhancing Salmonella Inhibition in Black Soldier Fly Larvae (Hermetia illucens L.) Conversion by Bioaugmentation With Gut Microbiota.

Yuanpu Zhang, Wen Chen, Binbin Wang, Kashif Ur Rehman, Arnold van Huis, Ahmed R Henawy, Minmin Cai, Longyu Zheng, Zhuqing Ren, Feng Huang and 1 more

Abstract read
In one paragraph

Article in Microbial biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

11 authors.

Yuanpu ZhangNational Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, National Engineering Research Center of Microbial Pesticides, Huazhong Agricultural University, Wuhan, China.
Wen ChenNational Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, National Engineering Research Center of Microbial Pesticides, Huazhong Agricultural University, Wuhan, China.
Binbin WangNational Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, National Engineering Research Center of Microbial Pesticides, Huazhong Agricultural University, Wuhan, China.
Kashif Ur RehmanGerman Institute of Food Technologies (DIL e.V.), Quakenbrück, Germany.
Arnold van HuisLaboratory of Entomology, Wageningen University & Research, Wageningen, the Netherlands.
Ahmed R HenawyNational Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, National Engineering Research Center of Microbial Pesticides, Huazhong Agricultural University, Wuhan, China.
Minmin CaiNational Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, National Engineering Research Center of Microbial Pesticides, Huazhong Agricultural University, Wuhan, China.ORCID 0000-0002-9613-7778
Longyu ZhengNational Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, National Engineering Research Center of Microbial Pesticides, Huazhong Agricultural University, Wuhan, China.
Zhuqing RenFrontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, China.
Feng HuangNational Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, National Engineering Research Center of Microbial Pesticides, Huazhong Agricultural University, Wuhan, China.
Jibin ZhangNational Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, National Engineering Research Center of Microbial Pesticides, Huazhong Agricultural University, Wuhan, China.ORCID 0000-0003-0788-557X

Funding

Fundamental Research Funds for the Central Universities 2662022SKYJ006Fundamental Research Funds for the Central Universities 2662023DKPY003Hubei Province Technological Innovation Plan Project 2024BCA006Major Project of Hubei Hongshan Laboratory 2022hszd013National Natural Science Foundation of China 31770136
6 · The paper itself

Abstract

Black soldier fly larvae (BSFL) can efficiently convert organic waste into biomass and reduce pathogenic bacteria in organic waste. The microbial composition of the substrate and the gut of BSFL is a pivotal factor in determining the efficacy of BSFL in pathogen elimination. However, there are insufficient data on the gut microbiology of BSFL in relation to pathogen inhibition. To address this gap, we investigated the dynamics of Salmonella during the conversion of chicken manure by BSFL and examined the role of intestinal bacterial communities and core bacteria in reducing Salmonella levels. The results indicate that BSFL treatment can reduce the amount of Salmonella in chicken manure, with the gut microbiome of the BSFL playing a crucial role in this reduction. Combining metagenomic analysis with culturomics methods, we isolated 158 strains from the larval gut, in which seven gut bacteria belonging to the genus Bacillus can promote BSFL to reduce Salmonella. In reinoculation and validation experiments, the combination of BSFL and Bacillus velezensis A2 enhanced the elimination of Salmonella from chicken manure and larvae. This study provides insight into how BSFL can reduce pathogenic bacteria in chicken manure and suggests that pairing BSFL with functional microorganisms can improve the biosafety of organic waste conversion by BSFL.

Indexed as

AntibiosisDipteraGastrointestinal MicrobiomeSalmonellaAnimalsBacillusBacteriaChickensLarvaManureMetagenomicsManurebioconversionfunctional microorganismsHermetia illucensorganic wastezoonotic pathogens

Identifiers

PMID41428602
PMCPMC12721473

What OpenQuestion holds

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Registered trials

None linked

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.