Pub Date : 2024-07-15DOI: 10.3389/fmicb.2024.1443283
Xiangyu Meng, Nan Tang, Wenfeng Su, Weiji Chen, Yue Zhang, He Li
DaiDai fruit, a medicinal and edible plant fruit, is abundant in biologically active compounds and has a long history of use in traditional Chinese medicine. This research focuses on utilizing fermentation to develop a functional DaiDai fruit fermentation broth. Lactobacillus, Bacillus subtilis and Saccharomyces cerevisiae were employed in the fermentation process. By conducting screenings of bacterial strains, single factor experiments, and response surface methodology, the total flavonoids, polysaccharides, polyphenols, and 1,1-diphenyl-2-trinitrophenylhydrazine (DPPH) free radical scavenging rate were used as the index for selection, ultimately identifying Lactobacillus L-13 as the optimal fermentation strain. The optimal fermentation conditions were determined to be a time of 108 h, a temperature of 43.6°C, and a solid–liquid ratio of 1:15.157 (w/v). Under these conditions, the total flavonoid content reached 412.01 mg/g, representing a 36.71% increase compared to conventional extraction methods. The contents of polysaccharides and polyphenols and the DPPH scavenging rate were also increased. The fermentation broth of DaiDai fruit exhibited inhibitory effects on tyrosinase and melanin production in mouse melanoma cells B16-F10 induced by α-MSH and anti-inflammatory properties in a zebrafish inflammation model. These indicate that the DaiDai fruit fermentation broth possesses anti-melanoma, whitening, and anti-inflammatory properties, showcasing significant potential for applications in medicine, cosmetics, and other industries.
{"title":"Fermentation of DaiDai fruit and its biological activity","authors":"Xiangyu Meng, Nan Tang, Wenfeng Su, Weiji Chen, Yue Zhang, He Li","doi":"10.3389/fmicb.2024.1443283","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1443283","url":null,"abstract":"DaiDai fruit, a medicinal and edible plant fruit, is abundant in biologically active compounds and has a long history of use in traditional Chinese medicine. This research focuses on utilizing fermentation to develop a functional DaiDai fruit fermentation broth. Lactobacillus, Bacillus subtilis and Saccharomyces cerevisiae were employed in the fermentation process. By conducting screenings of bacterial strains, single factor experiments, and response surface methodology, the total flavonoids, polysaccharides, polyphenols, and 1,1-diphenyl-2-trinitrophenylhydrazine (DPPH) free radical scavenging rate were used as the index for selection, ultimately identifying Lactobacillus L-13 as the optimal fermentation strain. The optimal fermentation conditions were determined to be a time of 108 h, a temperature of 43.6°C, and a solid–liquid ratio of 1:15.157 (w/v). Under these conditions, the total flavonoid content reached 412.01 mg/g, representing a 36.71% increase compared to conventional extraction methods. The contents of polysaccharides and polyphenols and the DPPH scavenging rate were also increased. The fermentation broth of DaiDai fruit exhibited inhibitory effects on tyrosinase and melanin production in mouse melanoma cells B16-F10 induced by α-MSH and anti-inflammatory properties in a zebrafish inflammation model. These indicate that the DaiDai fruit fermentation broth possesses anti-melanoma, whitening, and anti-inflammatory properties, showcasing significant potential for applications in medicine, cosmetics, and other industries.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141647838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.3389/fmicb.2024.1384463
Natalia Tyszkiewicz, J. Truu, Piotr Młynarz, Grzegorz Pasternak
Bioelectrochemical systems offer unique opportunities to remove recalcitrant environmental pollutants in a net positive energy process, although it remains challenging because of the toxic character of such compounds. In this study, microbial fuel cell (MFC) technology was applied to investigate the benzene degradation process for more than 160 days, where glucose was used as a co-metabolite and a control. We have applied an inoculation strategy that led to the development of 10 individual microbial communities. The electrochemical dynamics of MFC efficiency was observed, along with their 1H NMR metabolic fingerprints and analysis of the microbial community. The highest power density of 120 mW/m2 was recorded in the final period of the experiment when benzene/glucose was used as fuel. This is the highest value reported in a benzene/co-substrate system. Metabolite analysis confirmed the full removal of benzene, while the dominance of fermentation products indicated the strong occurrence of non-electrogenic reactions. Based on 16S rRNA gene amplicon sequencing, bacterial community analysis revealed several petroleum-degrading microorganisms, electroactive species and biosurfactant producers. The dominant species were recognised as Citrobacter freundii and Arcobacter faecis. Strong, positive impact of the presence of benzene on the alpha diversity was recorded, underlining the high complexity of the bioelectrochemically supported degradation of petroleum compounds. This study reveals the importance of supporting the bioelectrochemical degradation process with auxiliary substrates and inoculation strategies that allow the communities to reach sufficient diversity to improve the power output and degradation efficiency in MFCs beyond the previously known limits. This study, for the first time, provides an outlook on the syntrophic activity of biosurfactant producers and petroleum degraders towards the efficient removal and conversion of recalcitrant hydrophobic compounds into electricity in MFCs.
{"title":"The influence of benzene on the composition, diversity and performance of the anodic bacterial community in glucose-fed microbial fuel cells","authors":"Natalia Tyszkiewicz, J. Truu, Piotr Młynarz, Grzegorz Pasternak","doi":"10.3389/fmicb.2024.1384463","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1384463","url":null,"abstract":"Bioelectrochemical systems offer unique opportunities to remove recalcitrant environmental pollutants in a net positive energy process, although it remains challenging because of the toxic character of such compounds. In this study, microbial fuel cell (MFC) technology was applied to investigate the benzene degradation process for more than 160 days, where glucose was used as a co-metabolite and a control. We have applied an inoculation strategy that led to the development of 10 individual microbial communities. The electrochemical dynamics of MFC efficiency was observed, along with their 1H NMR metabolic fingerprints and analysis of the microbial community. The highest power density of 120 mW/m2 was recorded in the final period of the experiment when benzene/glucose was used as fuel. This is the highest value reported in a benzene/co-substrate system. Metabolite analysis confirmed the full removal of benzene, while the dominance of fermentation products indicated the strong occurrence of non-electrogenic reactions. Based on 16S rRNA gene amplicon sequencing, bacterial community analysis revealed several petroleum-degrading microorganisms, electroactive species and biosurfactant producers. The dominant species were recognised as Citrobacter freundii and Arcobacter faecis. Strong, positive impact of the presence of benzene on the alpha diversity was recorded, underlining the high complexity of the bioelectrochemically supported degradation of petroleum compounds. This study reveals the importance of supporting the bioelectrochemical degradation process with auxiliary substrates and inoculation strategies that allow the communities to reach sufficient diversity to improve the power output and degradation efficiency in MFCs beyond the previously known limits. This study, for the first time, provides an outlook on the syntrophic activity of biosurfactant producers and petroleum degraders towards the efficient removal and conversion of recalcitrant hydrophobic compounds into electricity in MFCs.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141647822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Transforming coniferous plantation into broadleaved or mixed broadleaved-coniferous plantations is the tendency of forest management strategies in subtropical China. However, the effects of this conversion on soil phosphorus (P) cycling microbial functional genes are still unknown.Soil samples were collected from 0–20, 20–40, and 40–60 cm (topsoil, middle layer, and subsoil, respectively) under coniferous Pinus massoniana (PM), broadleaved Erythrophleum fordii (EF), and their mixed (PM/EF) plantation in subtropical China. Used metagenomic sequencing to examine the alterations of relative abundances and molecular ecological network structure of soil P-cycling functional genes after the conversion of plantations.The composition of P-cycling genes in the topsoil of PM stand was significantly different from that of PM/EF and EF stands (p < 0.05), and total phosphorus (TP) was the main factor causing this difference. After transforming PM plantation into EF plantation, the relative abundances of P solubilization and mineralization genes significantly increased in the topsoil and middle layer with the decrease of soil TP content. The abundances of P-starvation response regulation genes also significantly increased in the subsoil (p < 0.05), which may have been influenced by soil organic carbon (SOC). The dominant genes in all soil layers under three plantations were phoR, glpP, gcd, ppk, and ppx. Transforming PM into EF plantation apparently increased gcd abundance in the topsoil (p < 0.05), with TP and NO3−-N being the main influencing factors. After transforming PM into PM/EF plantations, the molecular ecological network structure of P-cycling genes was more complex; moreover, the key genes in the network were modified with the transformation of PM plantation.Transforming PM into EF plantation mainly improved the phosphate solubilizing potential of microorganisms at topsoil, while transforming PM into PM/EF plantation may have enhanced structural stability of microbial P-cycling genes react to environmental changes.
将针叶林改造成阔叶林或阔叶林-针叶林混交林是中国亚热带森林经营战略的趋势。本研究采集了中国亚热带针叶林Pinus massoniana(PM)、阔叶林Erythrophleum fordii(EF)及其混交林(PM/EF)下0-20、20-40和40-60厘米(表土、中层和底土)的土壤样品。利用元基因组测序技术研究了种植园改造后土壤P循环功能基因相对丰度和分子生态网络结构的变化。PM种植园表土中P循环基因的组成与PM/EF和EF种植园表土中P循环基因的组成有显著差异(p < 0.05),总磷(TP)是造成这种差异的主要因素。将 PM 种植区改造为 EF 种植区后,随着土壤 TP 含量的降低,表层和中层土壤中 P 溶解和矿化基因的相对丰度明显增加。底土中 P-饥饿响应调控基因的丰度也明显增加(p < 0.05),这可能受到土壤有机碳(SOC)的影响。将 PM 改造成 EF 后,表层土壤中 gcd 的丰度明显增加(p < 0.05),主要影响因素是 TP 和 NO3--N。将PM转化为PM/EF种植园后,P循环基因的分子生态网络结构更加复杂,而且网络中的关键基因也随着PM种植园的转化而发生了改变。
{"title":"Soil phosphorus cycling microbial functional genes of monoculture and mixed plantations of native tree species in subtropical China","authors":"Lin Qin, Zhirou Xiao, Angang Ming, Jinqian Teng, Hao Zhu, Jiaqi Qin, Zeli Liang","doi":"10.3389/fmicb.2024.1419645","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1419645","url":null,"abstract":"Transforming coniferous plantation into broadleaved or mixed broadleaved-coniferous plantations is the tendency of forest management strategies in subtropical China. However, the effects of this conversion on soil phosphorus (P) cycling microbial functional genes are still unknown.Soil samples were collected from 0–20, 20–40, and 40–60 cm (topsoil, middle layer, and subsoil, respectively) under coniferous Pinus massoniana (PM), broadleaved Erythrophleum fordii (EF), and their mixed (PM/EF) plantation in subtropical China. Used metagenomic sequencing to examine the alterations of relative abundances and molecular ecological network structure of soil P-cycling functional genes after the conversion of plantations.The composition of P-cycling genes in the topsoil of PM stand was significantly different from that of PM/EF and EF stands (p < 0.05), and total phosphorus (TP) was the main factor causing this difference. After transforming PM plantation into EF plantation, the relative abundances of P solubilization and mineralization genes significantly increased in the topsoil and middle layer with the decrease of soil TP content. The abundances of P-starvation response regulation genes also significantly increased in the subsoil (p < 0.05), which may have been influenced by soil organic carbon (SOC). The dominant genes in all soil layers under three plantations were phoR, glpP, gcd, ppk, and ppx. Transforming PM into EF plantation apparently increased gcd abundance in the topsoil (p < 0.05), with TP and NO3−-N being the main influencing factors. After transforming PM into PM/EF plantations, the molecular ecological network structure of P-cycling genes was more complex; moreover, the key genes in the network were modified with the transformation of PM plantation.Transforming PM into EF plantation mainly improved the phosphate solubilizing potential of microorganisms at topsoil, while transforming PM into PM/EF plantation may have enhanced structural stability of microbial P-cycling genes react to environmental changes.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.3389/fmicb.2024.1357372
Ya-nan Wang, Yu-ting Wu, Ling Cao, Wen-quan Niu
Metagenomic next-generation sequencing (mNGS) was used to analyze the etiological distribution of refractory pneumonia in children. We compared its efficacy in pathogen diagnosis against traditional methods to provide a basis for clinical adjustment and treatment.A total of 60 children with refractory pneumonia treated at the Department of Respiratory Medicine, Children’s Hospital Affiliated with the Capital Institute of Paediatrics, from September 2019 to December 2021 were enrolled in this study. Clinical data (including sex, age, laboratory tests, complications, and discharge diagnosis) and lower respiratory tract specimens were collected, including bronchoalveolar lavage fluid (BALF), deep sputum, pleural effusion, lung abscess puncture fluid, traditional respiratory pathogens (culture, acid-fast staining, polymerase chain reaction, serological testing, etc.), and mNGS detection methods were used to determine the distribution of pathogens in children with refractory pneumonia and to compare the positive rate and diagnostic efficiency of mNGS and traditional pathogen detection for different types of pathogens.Among the 60 children with refractory pneumonia, 43 specimens were positive by mNGS, and 67 strains of pathogens were detected, including 20.90% (14 strains) of which were Mycoplasma pneumoniae, 11.94% (8 strains) were Streptococcus pneumoniae, 7.46% (5 strains) were cytomegalovirus, and 5.97% (4 strains) were Candida albicans. Thirty-nine strains of Mycoplasma pneumoniae (41.03%, 16 strains), Streptococcus pneumoniae (10.26%, 4 strains), Candida albicans (7.69%, 3 strains), and Aspergillus (5.13%, 2 strains) were detected using traditional methods. The positive rate of mNGS detection was 90.48%, and the positive rate of the traditional method was 61.90% (p = 0.050), especially for G+ bacteria. The positive rate of mNGS was greater than that of traditional methods (p < 0.05), but they had no significant difference in detecting G- bacteria, viruses, fungi, or Mycoplasma/Chlamydia. Among the 60 patients, 21 had mixed infections, 25 had single infections, and the other 14 had unknown pathogens. Mycoplasma pneumoniae was most common in both mixed infections and single infections. The sensitivity, specificity, positive predictive value, and negative predictive value of mNGS were 95.45, 37.50, 80.77, and 75.00%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of the traditional methods were 72.72, 62.50, 84.21, and 45.45%, respectively. The clinical compliance of mNGS was 80.00%, and that of the traditional method was 70.00%. The sensitivity and negative predictive value of mNGS were high, and the difference in the sensitivity for detecting G+ bacteria was statistically significant (p < 0.05). However, the differences in G- bacteria, fungi, and Mycoplasma/Chlamydia were not statistically significant (p > 0.05). Due to the small sample size, statistical analysis could not be conducted on viral
{"title":"Application of metagenomic next-generation sequencing in the etiological diagnosis of refractory pneumonia in children","authors":"Ya-nan Wang, Yu-ting Wu, Ling Cao, Wen-quan Niu","doi":"10.3389/fmicb.2024.1357372","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1357372","url":null,"abstract":"Metagenomic next-generation sequencing (mNGS) was used to analyze the etiological distribution of refractory pneumonia in children. We compared its efficacy in pathogen diagnosis against traditional methods to provide a basis for clinical adjustment and treatment.A total of 60 children with refractory pneumonia treated at the Department of Respiratory Medicine, Children’s Hospital Affiliated with the Capital Institute of Paediatrics, from September 2019 to December 2021 were enrolled in this study. Clinical data (including sex, age, laboratory tests, complications, and discharge diagnosis) and lower respiratory tract specimens were collected, including bronchoalveolar lavage fluid (BALF), deep sputum, pleural effusion, lung abscess puncture fluid, traditional respiratory pathogens (culture, acid-fast staining, polymerase chain reaction, serological testing, etc.), and mNGS detection methods were used to determine the distribution of pathogens in children with refractory pneumonia and to compare the positive rate and diagnostic efficiency of mNGS and traditional pathogen detection for different types of pathogens.Among the 60 children with refractory pneumonia, 43 specimens were positive by mNGS, and 67 strains of pathogens were detected, including 20.90% (14 strains) of which were Mycoplasma pneumoniae, 11.94% (8 strains) were Streptococcus pneumoniae, 7.46% (5 strains) were cytomegalovirus, and 5.97% (4 strains) were Candida albicans. Thirty-nine strains of Mycoplasma pneumoniae (41.03%, 16 strains), Streptococcus pneumoniae (10.26%, 4 strains), Candida albicans (7.69%, 3 strains), and Aspergillus (5.13%, 2 strains) were detected using traditional methods. The positive rate of mNGS detection was 90.48%, and the positive rate of the traditional method was 61.90% (p = 0.050), especially for G+ bacteria. The positive rate of mNGS was greater than that of traditional methods (p < 0.05), but they had no significant difference in detecting G- bacteria, viruses, fungi, or Mycoplasma/Chlamydia. Among the 60 patients, 21 had mixed infections, 25 had single infections, and the other 14 had unknown pathogens. Mycoplasma pneumoniae was most common in both mixed infections and single infections. The sensitivity, specificity, positive predictive value, and negative predictive value of mNGS were 95.45, 37.50, 80.77, and 75.00%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of the traditional methods were 72.72, 62.50, 84.21, and 45.45%, respectively. The clinical compliance of mNGS was 80.00%, and that of the traditional method was 70.00%. The sensitivity and negative predictive value of mNGS were high, and the difference in the sensitivity for detecting G+ bacteria was statistically significant (p < 0.05). However, the differences in G- bacteria, fungi, and Mycoplasma/Chlamydia were not statistically significant (p > 0.05). Due to the small sample size, statistical analysis could not be conducted on viral","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.3389/fmicb.2024.1433892
Yi Lu, Xiaobing Cai, Baohua Shi, Haitao Gong
Osteoporosis, characterized by reduced bone density and heightened fracture risk, is influenced by genetic and environmental factors. This study investigates the interplay between gut microbiota, plasma metabolomics, and osteoporosis, identifying potential causal relationships mediated by plasma metabolites.Utilizing aggregated genome-wide association studies (GWAS) data, a comprehensive two-sample Mendelian Randomization (MR) analysis was performed involving 196 gut microbiota taxa, 1,400 plasma metabolites, and osteoporosis indicators. Causal relationships between gut microbiota, plasma metabolites, and osteoporosis were explored.The MR analyses revealed ten gut microbiota taxa associated with osteoporosis, with five taxa positively linked to increased risk and five negatively associated. Additionally, 96 plasma metabolites exhibited potential causal relationships with osteoporosis, with 49 showing positive associations and 47 displaying negative associations. Mediation analyses identified six causal pathways connecting gut microbiota to osteoporosis through ten mediating relationships involving seven distinct plasma metabolites, two of which demonstrated suppression effects.This study provides suggestive evidence of genetic correlations and causal links between gut microbiota, plasma metabolites, and osteoporosis. The findings underscore the complex, multifactorial nature of osteoporosis and suggest the potential of gut microbiota and plasma metabolite profiles as biomarkers or therapeutic targets in the management of osteoporosis.
{"title":"Gut microbiota, plasma metabolites, and osteoporosis: unraveling links via Mendelian randomization","authors":"Yi Lu, Xiaobing Cai, Baohua Shi, Haitao Gong","doi":"10.3389/fmicb.2024.1433892","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1433892","url":null,"abstract":"Osteoporosis, characterized by reduced bone density and heightened fracture risk, is influenced by genetic and environmental factors. This study investigates the interplay between gut microbiota, plasma metabolomics, and osteoporosis, identifying potential causal relationships mediated by plasma metabolites.Utilizing aggregated genome-wide association studies (GWAS) data, a comprehensive two-sample Mendelian Randomization (MR) analysis was performed involving 196 gut microbiota taxa, 1,400 plasma metabolites, and osteoporosis indicators. Causal relationships between gut microbiota, plasma metabolites, and osteoporosis were explored.The MR analyses revealed ten gut microbiota taxa associated with osteoporosis, with five taxa positively linked to increased risk and five negatively associated. Additionally, 96 plasma metabolites exhibited potential causal relationships with osteoporosis, with 49 showing positive associations and 47 displaying negative associations. Mediation analyses identified six causal pathways connecting gut microbiota to osteoporosis through ten mediating relationships involving seven distinct plasma metabolites, two of which demonstrated suppression effects.This study provides suggestive evidence of genetic correlations and causal links between gut microbiota, plasma metabolites, and osteoporosis. The findings underscore the complex, multifactorial nature of osteoporosis and suggest the potential of gut microbiota and plasma metabolite profiles as biomarkers or therapeutic targets in the management of osteoporosis.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.3389/fmicb.2024.1429179
Xuerong Sun, Robert J. W. Brewin, Christian Hacker, Johannes J. Viljoen, Mengyu Li
The community structure and ecological function of marine ecosystems are critically dependent on phytoplankton. However, our understanding of phytoplankton is limited due to the lack of detailed information on their morphology. To address this gap, we developed a framework that combines scanning electron microscopy (SEM) with photogrammetry to create realistic 3D (three-dimensional) models of phytoplankton. The workflow of this framework is demonstrated using two marine algal species, one dinoflagellate Prorocentrum micans and one diatom Halamphora sp. The resulting 3D models are made openly available and allow users to interact with phytoplankton and their complex structures virtually (digitally) and tangibly (3D printing). They also allow for surface area and biovolume calculations of phytoplankton, as well as the exploration of their light scattering properties, which are both important for ecosystem modeling. Additionally, by presenting these models to the public, it bridges the gap between scientific inquiry and education, promoting broader awareness on the importance of phytoplankton.
{"title":"Generating open-source 3D phytoplankton models by integrating photogrammetry with scanning electron microscopy","authors":"Xuerong Sun, Robert J. W. Brewin, Christian Hacker, Johannes J. Viljoen, Mengyu Li","doi":"10.3389/fmicb.2024.1429179","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1429179","url":null,"abstract":"The community structure and ecological function of marine ecosystems are critically dependent on phytoplankton. However, our understanding of phytoplankton is limited due to the lack of detailed information on their morphology. To address this gap, we developed a framework that combines scanning electron microscopy (SEM) with photogrammetry to create realistic 3D (three-dimensional) models of phytoplankton. The workflow of this framework is demonstrated using two marine algal species, one dinoflagellate Prorocentrum micans and one diatom Halamphora sp. The resulting 3D models are made openly available and allow users to interact with phytoplankton and their complex structures virtually (digitally) and tangibly (3D printing). They also allow for surface area and biovolume calculations of phytoplankton, as well as the exploration of their light scattering properties, which are both important for ecosystem modeling. Additionally, by presenting these models to the public, it bridges the gap between scientific inquiry and education, promoting broader awareness on the importance of phytoplankton.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.3389/fmicb.2024.1419686
Shiyu Sun, Huiqiong Zhang, Linying Ye, Litao Huang, Jieyu Du, Xiaomin Liang, Xiaofeng Zhang, Jiaxing Chen, Yingping Jiang, Ling Chen
Revealing individual characteristics is supportive for identifying individuals in forensic crime. As saliva is one of the most common biological samples used in crime scenes, it is important to make full use of the rich individual information contained in saliva. The aim of this study was to explore the application of the microbiome in forensic science by analysing differences in the salivary microbiome and metabolome of healthy individuals with different dietary habits.We performed 16S rDNA sequencing analysis based on oral saliva samples collected from 12 vegetarians, 12 seafood omnivores and 12 beef and lamb omnivores. Non-targeted metabolomics analyses were also performed based on saliva samples from healthy individuals.The results showed that the dominant flora of vegetarians was dominated by Neisseria (belonging to the phylum Proteobacteria), while seafood omnivores and beef and lamb omnivores were dominated by Streptococcus (belonging to the phylum Firmicutes). NDMS-based and cluster analyses showed that vegetarian dieters were significantly differentiated from meat dieters (seafood omnivores and beef and lamb omnivores), which may be related to the fact that high-fiber diets can create a different salivary flora structure. Variants were also detected in salivary metabolic pathways, including positive correlations with Lipid metabolism, Amino acid metabolism, Carbohydrate metabolism, and Nucleotide metabolism in vegetarians, and correlations in seafood omnivores. In order to select salivary microorganisms and metabolic markers that can distinguish different dietary profiles, a random forest classifier model was constructed in this study, and the results showed that individuals with different dietary profiles could be successfully distinguished based on the core genera and metabolites such as Streptococcus, Histidinyl-Valine.Our study provides a supportive basis for the application of salivary polyomics in order to reveal the dietary characteristics of individuals for forensic investigation and crime solving.
{"title":"Combined analysis of the microbiome and metabolome to reveal the characteristics of saliva from different diets: a comparison among vegans, seafood-based omnivores, and red meat (beef and lamb) omnivores","authors":"Shiyu Sun, Huiqiong Zhang, Linying Ye, Litao Huang, Jieyu Du, Xiaomin Liang, Xiaofeng Zhang, Jiaxing Chen, Yingping Jiang, Ling Chen","doi":"10.3389/fmicb.2024.1419686","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1419686","url":null,"abstract":"Revealing individual characteristics is supportive for identifying individuals in forensic crime. As saliva is one of the most common biological samples used in crime scenes, it is important to make full use of the rich individual information contained in saliva. The aim of this study was to explore the application of the microbiome in forensic science by analysing differences in the salivary microbiome and metabolome of healthy individuals with different dietary habits.We performed 16S rDNA sequencing analysis based on oral saliva samples collected from 12 vegetarians, 12 seafood omnivores and 12 beef and lamb omnivores. Non-targeted metabolomics analyses were also performed based on saliva samples from healthy individuals.The results showed that the dominant flora of vegetarians was dominated by Neisseria (belonging to the phylum Proteobacteria), while seafood omnivores and beef and lamb omnivores were dominated by Streptococcus (belonging to the phylum Firmicutes). NDMS-based and cluster analyses showed that vegetarian dieters were significantly differentiated from meat dieters (seafood omnivores and beef and lamb omnivores), which may be related to the fact that high-fiber diets can create a different salivary flora structure. Variants were also detected in salivary metabolic pathways, including positive correlations with Lipid metabolism, Amino acid metabolism, Carbohydrate metabolism, and Nucleotide metabolism in vegetarians, and correlations in seafood omnivores. In order to select salivary microorganisms and metabolic markers that can distinguish different dietary profiles, a random forest classifier model was constructed in this study, and the results showed that individuals with different dietary profiles could be successfully distinguished based on the core genera and metabolites such as Streptococcus, Histidinyl-Valine.Our study provides a supportive basis for the application of salivary polyomics in order to reveal the dietary characteristics of individuals for forensic investigation and crime solving.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141645494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Compared with 454 sequencing technology, short-read sequencing (e.g., Illumina) technology generates sequences of high accuracy, but limited length (<500 bp). Such a limitation can prove that studying a target gene using a large amplicon (>500 bp) is challenging. The ammonia monooxygenase subunit A (amoA) gene of ammonia-oxidizing archaea (AOA), which plays a crucial part in the nitrification process, is such a gene. By providing a full overview of the community of a functional microbial guild, 16S ribosomal ribonucleic acid (rRNA) gene sequencing could overcome this problem. However, it remains unclear how 16S rRNA primer selection influences the quantification of relative abundance and the identification of community composition of nitrifiers, especially AOA. In the present study, a comparison was made between the performance of primer pairs 338F-806R, 515F-806R, and 515F-907R to a shotgun metagenome approach. The structure of nitrifier communities subjected to different long-term organic matter amendment and water management protocols was assessed. Overall, we observed higher Chao1 richness diversity of soil total bacteria by using 515F-806R compared to 338F-806R and 515F-907R, while higher Pielou’s evenness diversity was observed by using 515F-806R and 515F-907R compared to 338F-806R. The studied primer pairs revealed different performances on the relative abundance of Thaumarchaeota, AOB, and NOB. The Thaumarchaeota 16S rRNA sequence was rarely detected using 338F-806R, while the relative abundances of Thaumarchaeota detected using 515F-806R were higher than those detected by using 515F-907R. AOB showed higher proportions in the 338F-806R and 515F-907R data, than in 515F-806R data. Different primers pairs showed significant change in relative proportion of NOB. Nonetheless, we found consistent patterns of the phylotype distribution of nitrifiers in different treatments. Nitrosopumilales (NP) and Nitrososphaerales (NS) clades were the dominant members of the AOA community in soils subject to controlled irrigation, whereas Ca. Nitrosotaleales (NT) and NS clades dominated the AOA community in soils subject to flooding irrigation. Nitrospira lineage II was the dominant NOB phylotype in all samples. Overall, ideal 16S rRNA primer pairs were identified for the analysis of nitrifier communities. Moreover, NP and NT clades of AOA might have distinct environmental adaptation strategies under different irrigation treatments.
{"title":"Comparative evaluation of 16S rRNA primer pairs in identifying nitrifying guilds in soils under long-term organic fertilization and water management","authors":"Xue Zhou, Xiaoyin Liu, Meiyu Liu, Weixuan Liu, Junzeng Xu, Yawei Li","doi":"10.3389/fmicb.2024.1424795","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1424795","url":null,"abstract":"Compared with 454 sequencing technology, short-read sequencing (e.g., Illumina) technology generates sequences of high accuracy, but limited length (<500 bp). Such a limitation can prove that studying a target gene using a large amplicon (>500 bp) is challenging. The ammonia monooxygenase subunit A (amoA) gene of ammonia-oxidizing archaea (AOA), which plays a crucial part in the nitrification process, is such a gene. By providing a full overview of the community of a functional microbial guild, 16S ribosomal ribonucleic acid (rRNA) gene sequencing could overcome this problem. However, it remains unclear how 16S rRNA primer selection influences the quantification of relative abundance and the identification of community composition of nitrifiers, especially AOA. In the present study, a comparison was made between the performance of primer pairs 338F-806R, 515F-806R, and 515F-907R to a shotgun metagenome approach. The structure of nitrifier communities subjected to different long-term organic matter amendment and water management protocols was assessed. Overall, we observed higher Chao1 richness diversity of soil total bacteria by using 515F-806R compared to 338F-806R and 515F-907R, while higher Pielou’s evenness diversity was observed by using 515F-806R and 515F-907R compared to 338F-806R. The studied primer pairs revealed different performances on the relative abundance of Thaumarchaeota, AOB, and NOB. The Thaumarchaeota 16S rRNA sequence was rarely detected using 338F-806R, while the relative abundances of Thaumarchaeota detected using 515F-806R were higher than those detected by using 515F-907R. AOB showed higher proportions in the 338F-806R and 515F-907R data, than in 515F-806R data. Different primers pairs showed significant change in relative proportion of NOB. Nonetheless, we found consistent patterns of the phylotype distribution of nitrifiers in different treatments. Nitrosopumilales (NP) and Nitrososphaerales (NS) clades were the dominant members of the AOA community in soils subject to controlled irrigation, whereas Ca. Nitrosotaleales (NT) and NS clades dominated the AOA community in soils subject to flooding irrigation. Nitrospira lineage II was the dominant NOB phylotype in all samples. Overall, ideal 16S rRNA primer pairs were identified for the analysis of nitrifier communities. Moreover, NP and NT clades of AOA might have distinct environmental adaptation strategies under different irrigation treatments.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141645789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using microorganisms as biocontrol agents against soilborne plant pathogens is a promising alternative to chemical pesticides. However, only some biocontrol agents have proven effective under field conditions. This study explores the potential of highly resilient microalgae isolated from harsh environments, such as Biological Soil Crusts and agricultural fields in semi-arid regions, as a novel and sustainable approach to biocontrol. Fifty-nine microalgal strains, including thirteen cyanobacteria and forty-six green algae, were isolated and identified. Dual-culture plate assays and toxicity tests of microalgal growth media were conducted to evaluate the antifungal activity of the isolates against eight representative soilborne pathogens. The results showed that many microalgae strains exhibited significant inhibitory effects on the growth of specific fungal pathogens, although the activity varied among different microalgal strains and pathogen species. Some strains even promoted the growth of certain fungi. The lack of a clear pattern in the antifungal activity highlights the complexity and specificity of the interactions between microalgae and soilborne pathogens. An “Inhibition Effectiveness” metric was developed to quantify biocontrol potential based on fungal growth inhibition. The green algal genus Desmodesmus, particularly Desmodesmus subspicatus isolates, showed higher antifungal efficacy than other genera. While the inhibitory mechanisms remain unclear, the results demonstrate the promising biocontrol capabilities of microalgae from extreme environments like BSCs. Further research could unlock novel opportunities for sustainable disease management by harnessing specific microalgal strains or synergistic strain combinations targeting soilborne pathogens.
{"title":"Towards sustainable biocontrol: inhibition of soil borne fungi by microalgae from harsh environments","authors":"Dikla Eckstien, Noga Maximov, Nofet Margolis, Hagai Raanan","doi":"10.3389/fmicb.2024.1433765","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1433765","url":null,"abstract":"Using microorganisms as biocontrol agents against soilborne plant pathogens is a promising alternative to chemical pesticides. However, only some biocontrol agents have proven effective under field conditions. This study explores the potential of highly resilient microalgae isolated from harsh environments, such as Biological Soil Crusts and agricultural fields in semi-arid regions, as a novel and sustainable approach to biocontrol. Fifty-nine microalgal strains, including thirteen cyanobacteria and forty-six green algae, were isolated and identified. Dual-culture plate assays and toxicity tests of microalgal growth media were conducted to evaluate the antifungal activity of the isolates against eight representative soilborne pathogens. The results showed that many microalgae strains exhibited significant inhibitory effects on the growth of specific fungal pathogens, although the activity varied among different microalgal strains and pathogen species. Some strains even promoted the growth of certain fungi. The lack of a clear pattern in the antifungal activity highlights the complexity and specificity of the interactions between microalgae and soilborne pathogens. An “Inhibition Effectiveness” metric was developed to quantify biocontrol potential based on fungal growth inhibition. The green algal genus Desmodesmus, particularly Desmodesmus subspicatus isolates, showed higher antifungal efficacy than other genera. While the inhibitory mechanisms remain unclear, the results demonstrate the promising biocontrol capabilities of microalgae from extreme environments like BSCs. Further research could unlock novel opportunities for sustainable disease management by harnessing specific microalgal strains or synergistic strain combinations targeting soilborne pathogens.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.3389/fmicb.2024.1428304
Haiquan Kang, Ziling Wang, Jingfang Sun, Shuang Song, Lei Cheng, Yi Sun, Xingqi Pan, Changyu Wu, Ping Gong, Hongchun Li
Bloodstream infections (BSIs) are a critical medical concern, characterized by elevated morbidity, mortality, extended hospital stays, substantial healthcare costs, and diagnostic challenges. The clinical outcomes for patients with BSI can be markedly improved through the prompt identification of the causative pathogens and their susceptibility to antibiotics and antimicrobial agents. Traditional BSI diagnosis via blood culture is often hindered by its lengthy incubation period and its limitations in detecting pathogenic bacteria and their resistance profiles. Surface-enhanced Raman scattering (SERS) has recently gained prominence as a rapid and effective technique for identifying pathogenic bacteria and assessing drug resistance. This method offers molecular fingerprinting with benefits such as rapidity, sensitivity, and non-destructiveness. The objective of this study was to integrate deep learning (DL) with SERS for the rapid identification of common pathogens and their resistance to drugs in BSIs. To assess the feasibility of combining DL with SERS for direct detection, erythrocyte lysis and differential centrifugation were employed to isolate bacteria from blood samples with positive blood cultures. A total of 12,046 and 11,968 SERS spectra were collected from the two methods using Raman spectroscopy and subsequently analyzed using DL algorithms. The findings reveal that convolutional neural networks (CNNs) exhibit considerable potential in identifying prevalent pathogens and their drug-resistant strains. The differential centrifugation technique outperformed erythrocyte lysis in bacterial isolation from blood, achieving a detection accuracy of 98.68% for pathogenic bacteria and an impressive 99.85% accuracy in identifying carbapenem-resistant Klebsiella pneumoniae. In summary, this research successfully developed an innovative approach by combining DL with SERS for the swift identification of pathogenic bacteria and their drug resistance in BSIs. This novel method holds the promise of significantly improving patient prognoses and optimizing healthcare efficiency. Its potential impact could be profound, potentially transforming the diagnostic and therapeutic landscape of BSIs.
{"title":"Rapid identification of bloodstream infection pathogens and drug resistance using Raman spectroscopy enhanced by convolutional neural networks","authors":"Haiquan Kang, Ziling Wang, Jingfang Sun, Shuang Song, Lei Cheng, Yi Sun, Xingqi Pan, Changyu Wu, Ping Gong, Hongchun Li","doi":"10.3389/fmicb.2024.1428304","DOIUrl":"https://doi.org/10.3389/fmicb.2024.1428304","url":null,"abstract":"Bloodstream infections (BSIs) are a critical medical concern, characterized by elevated morbidity, mortality, extended hospital stays, substantial healthcare costs, and diagnostic challenges. The clinical outcomes for patients with BSI can be markedly improved through the prompt identification of the causative pathogens and their susceptibility to antibiotics and antimicrobial agents. Traditional BSI diagnosis via blood culture is often hindered by its lengthy incubation period and its limitations in detecting pathogenic bacteria and their resistance profiles. Surface-enhanced Raman scattering (SERS) has recently gained prominence as a rapid and effective technique for identifying pathogenic bacteria and assessing drug resistance. This method offers molecular fingerprinting with benefits such as rapidity, sensitivity, and non-destructiveness. The objective of this study was to integrate deep learning (DL) with SERS for the rapid identification of common pathogens and their resistance to drugs in BSIs. To assess the feasibility of combining DL with SERS for direct detection, erythrocyte lysis and differential centrifugation were employed to isolate bacteria from blood samples with positive blood cultures. A total of 12,046 and 11,968 SERS spectra were collected from the two methods using Raman spectroscopy and subsequently analyzed using DL algorithms. The findings reveal that convolutional neural networks (CNNs) exhibit considerable potential in identifying prevalent pathogens and their drug-resistant strains. The differential centrifugation technique outperformed erythrocyte lysis in bacterial isolation from blood, achieving a detection accuracy of 98.68% for pathogenic bacteria and an impressive 99.85% accuracy in identifying carbapenem-resistant Klebsiella pneumoniae. In summary, this research successfully developed an innovative approach by combining DL with SERS for the swift identification of pathogenic bacteria and their drug resistance in BSIs. This novel method holds the promise of significantly improving patient prognoses and optimizing healthcare efficiency. Its potential impact could be profound, potentially transforming the diagnostic and therapeutic landscape of BSIs.","PeriodicalId":509565,"journal":{"name":"Frontiers in Microbiology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141647599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}