Uneingeschränkter Zugang

Microbial Diversity and Screening for Potential Pathogens and Beneficial Bacteria of Five Jellyfish Species-Associated Microorganisms Based on 16S rRNA Sequencing

Liangzhi Li

Liangzhi Li

  • College of Marine Biological Resources and Management, Shanghai Ocean UniversityShanghai, China
  • Faculty of Naval Medicine, Naval Medical UniversityShanghai, China
Suche nach diesem Autor auf
Sciendo|Google Scholar
Li, Liangzhi
, 
Yina Zhu

Yina Zhu

Faculty of Naval Medicine, Naval Medical UniversityShanghai, China
Suche nach diesem Autor auf
Sciendo|Google Scholar
Zhu, Yina
, 
Feng Wu

Feng Wu

College of Marine Biological Resources and Management, Shanghai Ocean UniversityShanghai, China
Suche nach diesem Autor auf
Sciendo|Google Scholar
Wu, Feng
, 
Yuxin Shen

Yuxin Shen

Department of Radiation Oncology, Changhai Hospital, Naval Medical UniversityShanghai, China
Suche nach diesem Autor auf
Sciendo|Google Scholar
Shen, Yuxin
, 
Yi Wang

Yi Wang

College of Traditional Chinese Medicine, Jilin Agricultural UniversityChangchun, China
Suche nach diesem Autor auf
Sciendo|Google Scholar
Wang, Yi
, 
Juan Höfer

Juan Höfer

Escuela de Ciencias del Mar, Pontificia Universidad Católica de ValparaísoValparaíso, Chile
Suche nach diesem Autor auf
Sciendo|Google Scholar
Höfer, Juan
, 
Marina Pozzolini

Marina Pozzolini

Department of Earth, Environment and Life Sciences (DISTAV), University of GenovaGenova, Italy
Suche nach diesem Autor auf
Sciendo|Google Scholar
Pozzolini, Marina
, 
Mingke Wang

Mingke Wang

Department of Disease Control and Prevention, Naval Medical Center of PLA, Naval Medical UniversityShanghai, China
Suche nach diesem Autor auf
Sciendo|Google Scholar
Wang, Mingke
, 
Liang Xiao

Liang Xiao

Faculty of Naval Medicine, Naval Medical UniversityShanghai, China
Suche nach diesem Autor auf
Sciendo|Google Scholar
Xiao, Liang
 und 
Xiaojie Dai

Xiaojie Dai

College of Marine Biological Resources and Management, Shanghai Ocean UniversityShanghai, China
Suche nach diesem Autor auf
Sciendo|Google Scholar
Dai, Xiaojie
  
26. Aug. 2024
Microbial Diversity and Screening for Potential Pathogens and Beneficial Bacteria of Five Jellyfish Species-Associated Microorganisms Based on 16S rRNA Sequencing's Cover Image
Über diesen Artikel
Vorheriger Artikel
Nächster Artikel
Zitieren
COVER HERUNTERLADEN
Artikel-Kategorie: ORIGINAL PAPER
Online veröffentlicht: 26. Aug. 2024
Seitenbereich: 297 - 314
Eingereicht: 05. März 2024
Akzeptiert: 25. Mai 2024
DOI: https://doi.org/10.33073/pjm-2024-026
Schlüsselwörter
© 2024 Liangzhi Li et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Fig. 1.

Analysis of commensal microbial community compositions in five jellyfish species. A) From (a) to (e): Aurelia coerulea, Rhopilema esculentum, Phacellophora camtschatica, Cassiopea andromeda, and Chrysaora quinquecirrha; B) the microbial community compositions at the taxonomic level of the family for different jellyfish species. C) the shared and unique counts of microbial families among different jellyfish samples at the family level. D) the Circos relationship diagram depicting the top commensal microbial families corresponding to different jellyfish species based on their abundance. We selected the top 30 bacteria with the highest abundance and drew these figures.
Analysis of commensal microbial community compositions in five jellyfish species. A) From (a) to (e): Aurelia coerulea, Rhopilema esculentum, Phacellophora camtschatica, Cassiopea andromeda, and Chrysaora quinquecirrha; B) the microbial community compositions at the taxonomic level of the family for different jellyfish species. C) the shared and unique counts of microbial families among different jellyfish samples at the family level. D) the Circos relationship diagram depicting the top commensal microbial families corresponding to different jellyfish species based on their abundance. We selected the top 30 bacteria with the highest abundance and drew these figures.

Fig. 2.

Microbial community diversity analysis in five jellyfish species. A) Alpha diversity based on the Chao1 index; B) alpha diversity based on the Shannon index. C) alpha diversity based on the Simpson index; D) within-group PCA analysis among different jellyfish species; E) PCoA analysis among different jellyfish species; F) NMDS analysis among different jellyfish species. * – p < 0.05, ** – p < 0.01
Microbial community diversity analysis in five jellyfish species. A) Alpha diversity based on the Chao1 index; B) alpha diversity based on the Shannon index. C) alpha diversity based on the Simpson index; D) within-group PCA analysis among different jellyfish species; E) PCoA analysis among different jellyfish species; F) NMDS analysis among different jellyfish species. * – p < 0.05, ** – p < 0.01

Fig. 3.

Analysis of microbial community differences in the five jellyfish species. A) Evolutionary branching of the most abundant commensal microbial species from the order to genera level across the five jellyfish species. B) comparative differences in relative abundance among the top 14 families of commensal microbes at the family level; C) random forest analysis based on the mean decrease accuracy index. D) random forest analysis based on the mean decrease Gini index. We selected the dominant bacteria and drew these figures.
Analysis of microbial community differences in the five jellyfish species. A) Evolutionary branching of the most abundant commensal microbial species from the order to genera level across the five jellyfish species. B) comparative differences in relative abundance among the top 14 families of commensal microbes at the family level; C) random forest analysis based on the mean decrease accuracy index. D) random forest analysis based on the mean decrease Gini index. We selected the dominant bacteria and drew these figures.

Fig. 4.

The correlation network heatmap of commensal microbiota across the five species of jellyfish. (The red lines indicate positive correlations and blue lines for negative correlations). Solid lines represent significant differences, while dashed lines indicate non-significant differences. The thickness of the lines represents the relative abundance. We selected the top 20 bacteria and drew this figure.
The correlation network heatmap of commensal microbiota across the five species of jellyfish. (The red lines indicate positive correlations and blue lines for negative correlations). Solid lines represent significant differences, while dashed lines indicate non-significant differences. The thickness of the lines represents the relative abundance. We selected the top 20 bacteria and drew this figure.

Fig. 5.

Correlation analysis between the five jellyfish and their associated microbial communities. A-F) Correlation analysis between the associated jellyfish and microbial communities at different levels of taxonomical categories. RDA analysis was conducted using the top 10 abundant associated microbial communities across all samples.
Correlation analysis between the five jellyfish and their associated microbial communities. A-F) Correlation analysis between the associated jellyfish and microbial communities at different levels of taxonomical categories. RDA analysis was conducted using the top 10 abundant associated microbial communities across all samples.

Fig. 6.

Analysis of predicted gene functions and pathogenic phenotype prediction in microbial communities associated with five jellyfish species. A) Number of annotated genes unique and shared among different jellyfish samples; B) predicted pathogenic phenotype in microbial communities associated with different jellyfish species; C) differential analysis of predicted gene functions and metabolic pathways in microbial communities using STAMP analysis; D) composition of potential pathogenic bacterial communities across different jellyfish samples; E) composition of potential beneficial bacterial communities across different jellyfish samples. We selected the dominant bacteria and the top 30 genes with total expression levels from shared expression genes to draw these figures.
Analysis of predicted gene functions and pathogenic phenotype prediction in microbial communities associated with five jellyfish species. A) Number of annotated genes unique and shared among different jellyfish samples; B) predicted pathogenic phenotype in microbial communities associated with different jellyfish species; C) differential analysis of predicted gene functions and metabolic pathways in microbial communities using STAMP analysis; D) composition of potential pathogenic bacterial communities across different jellyfish samples; E) composition of potential beneficial bacterial communities across different jellyfish samples. We selected the dominant bacteria and the top 30 genes with total expression levels from shared expression genes to draw these figures.

Gene annotation and enriched pathways_

Entry Symbol Name Pathway or Brite
K00059 FabG, OAR1 3-oxoacyl-acyl carrier protein reductase fatty acid biosynthesis, prodigiosin biosynthesis, biotin metabolism, metabolic pathways, biosynthesis of secondary metabolites, fatty acid metabolism, biosynthesis of cofactors
K00257 mbtN, fadE14 acyl-acyl carrier protein dehydrogenase unclassified: metabolism
K00626 ACAT, atoB acetyl-CoA C-acetyltransferase fatty acid degradation, valine, leucine and isoleucine degradation, lysine degradation, benzoate degradation, tryptophan metabolism, pyruvate metabolism, glyoxylate and dicarboxylate metabolism, butanoate metabolism, carbon fixation pathways in prokaryotes, terpenoid backbone biosynthesis, metabolic pathways, biosynthesis of secondary metabolites, microbial metabolism in diverse environments, carbon metabolism, fatty acid metabolism, two-component system, fat digestion and absorption
K00799 GST, gst glutathione S-transferase glutathione metabolism, metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450, drug metabolism-other enzymes, metabolic pathways, platinum drug resistance, longevity regulating pathway-worm, pathways in cancer, chemical carcinogenesis-DNA adducts, chemical carcinogenesis-receptor activation, chemical carcinogenesis-reactive oxygen species, hepatocellular carcinoma, fluid shear stress and atherosclerosis
K01091 gph phosphoglycolate phosphatase glyoxylate and dicarboxylate metabolism, metabolic pathways, biosynthesis of secondary metabolites
K01652 ilvB, ilvG, ilvI acetolactatesynthase I/II/III large subunit valine, leucine and isoleucine biosynthesis, Butanoate metabolism, C5-branched dibasic acid metabolism, pantothenate and CoA biosynthesis, metabolic pathways, biosynthesis of secondary metabolites, 2-oxocarboxylic acid metabolism, biosynthesis of amino acids
K01784 galE, GALE UDP-glucose4-epimerase galactose metabolism, amino sugar and nucleotide sugar metabolism, O-antigen nucleotide sugar biosynthesis, metabolic pathways, biosynthesis of nucleotide sugars
K01897 ACSL, fadD long-chain acyl-CoA synthetase fatty acid biosynthesis, fatty acid degradation, metabolic pathways, fatty acid metabolism, quorum sensing, PPAR signaling pathway, peroxisome, ferroptosis, thermogenesis, adipocytokine signaling pathway
K01915 glnA, GLUL glutamine synthetase arginine biosynthesis, alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, nitrogen metabolism, metabolic pathways, microbial metabolism in diverse environments, biosynthesis of amino acids, two-component system, necroptosis, glutamatergic synapse, GABAergic synapse
K01990 ABC-2.A ABC-2 type transport system ATP-binding protein ABC transporters
K01992 ABC-2.P ABC-2 type transport system permease protein ABC transporters
K01995 livG branched-chain amino acid transport system ATP-bindin protein ABC transporters, quorum sensing
K01996 livF branched-chain amino acid transport system ATP-binding protein ABC transporters, quorum sensing
K01997 livH branched-chain amino acid transport system permease protein ABC transporters, quorum sensing
K01998 livM branched-chain amino acid transport system permease protein ABC transporters, quorum sensing
K01999 livK branched-chain amino acid transport system substrate-binding protein ABC transporters, quorum sensing
K02003 ABC.CD.A putative ABC transport system ATP-binding protein ABC transporters
K02004 ABC.CD.P putative ABC transport system permease protein ABC transporters
K02014 TC.FEV.OM iron complex outermembrane recepter protein other transporters
K02015 ABC.FEV.P iron complex transport system permease protein ABC transporters
K02016 ABC.FEV.S iron complex transport system substrate-binding protein ABC transporters
K02030 ABC.PA.S polar amino acid transport system substrate-binding protein ABC transporters
K02032 ABC.PE.A1 peptide/nickel transport system ATP-binding protein ABC transporters
K02035 ABC.PE.S peptide/nickel transport system substrate-binding protein ABC transporters
K03088 rpoE RNA polymerase sigma-70 factor, ECF subfamily transcription machinery (bacterial type)
K03406 mcp methyl-accepting chemotaxis protein two-component system, bacterial chemotaxis
K03704 cspA cold shock protein (beta-ribbon, CspA family) unclassified
K06147 ABCB-BAC ATP-binding cassette, subfamily B, bacterial ABC transporters
K07090 uncharacterized protein uncharacterized protein unclassified
K07107 ybgC acyl-CoA thioester hydrolase unclassified: metabolism
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
4 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Biologie, Mikrobiologie und Virologie
Zeitschrift RSS Feed