Dialister massiliensis sp. nov., a new bacterium isolated from the human gut

Afouda, Pamela; Dubourg, Grégory; Tomeï, Enora; Raoult, Didier; Fournier, Pierre‐Edouard

doi:10.1016/j.nmni.2020.100657

Cited by 6 publications

(6 citation statements)

References 14 publications

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“…Dialister spp. is common obligate anaerobes in the human microbiome ( 44 , 45 ), but in conflict with our results, Valles-Colomer et al ( 46 ) found that Dialister spp. was consistently depleted in humans with depression.…”

Section: Discussioncontrasting

confidence: 99%

Effects of ‘Healthy’ Fecal Microbiota Transplantation against the Deterioration of Depression in Fawn-Hooded Rats

Das

Lv³

et al. 2022

mSystems

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Section: Discussioncontrasting

confidence: 99%

Effects of ‘Healthy’ Fecal Microbiota Transplantation against the Deterioration of Depression in Fawn-Hooded Rats

Das

Lv³

et al. 2022

mSystems

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“…Dialister spp. are common obligate anaerobes in the human microbiome 44,45 , but in con ict with our results, Valles-Colomer et al found that Dialister spp. was consistently depleted in humans with depression 46 .…”

Section: Discussionsupporting

confidence: 69%

Amelioration of depressive symptoms on Fawn-Hooded rats through the 'healthy' fecal microbiota transplantation

Das

et al. 2021

Preprint

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Background : Depression is a recurrent, heterogeneous mood disorder, occurring in more than 260 million people worldwide. Gut microbiome dysbiosis is associated with the development of depressive-like behaviors by modulating neuro-biochemical metabolism through the microbiome-gut-brain (MGB) axis. Fecal microbiota transplantation (FMT) has been proposed as a potential therapeutic solution for depression, but the therapeutic efficiency and mechanism is unknown. Results : We performed FMT from Sprague-Dawley (SD) rats ('healthy' controls) to Fawn-hooded (FH) rats (depression model). Pre-FMT, the FH rats exhibited significantly elevated depressive behaviors and distinct neurotransmitter and cytokine levels compared with SD rats. Post-FMT, FH recipients receiving SD microbiota showed reduced depressive behaviors, a significant increase in hippocampal neurotransmitters and a significant decrease of some hippocampal cytokines compared to the ones receiving FH microbiota. SD-FMT resulted in the FH recipients' gut microbiome resembling the SD donor, and a significant shift in the serum metabolome but not the hippocampal metabolome. Conclusions : SD-FMT was inferred to ameliorate recipients' physiochemical features of depression via the significant decrease of gut microbial species such as Dialister sp., which led to the recipients' metabolic modulation in serum and hippocampus through the enteric nervous system, the intestinal barrier and the blood-brain barrier. Our results provided new data pointing to multiple mechanisms of interaction for the impact of gut microbiome modulation on depression therapy.

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“…On the other hand, Dialister massiliensis and D. micraerophilus have been previously described to produce valine arylamidase, an enzyme known to catalyse hydrolysis of N-terminal amino acids from peptides. 52,53 Prevotella and Sneathia have been widely recognized in biofilm formation, possibly explaining their association with valine in the present study. 54 The dramatic upregulation of valine in BV-positive women and its strong association with biofilm-forming bacterial species provide evidence for a possible mechanism of BV pathogenesis and would benefit from further research.…”

Section: Discussionsupporting

confidence: 51%

“…These findings validate the possible role of corynebacteria and C. metallidurans as normal vaginal inhabitants. On the other hand, Dialister massiliensis and D. micraerophilus have been previously described to produce valine arylamidase, an enzyme known to catalyse hydrolysis of N‐terminal amino acids from peptides 52,53 . Prevotella and Sneathia have been widely recognized in biofilm formation, possibly explaining their association with valine in the present study 54 .…”

Section: Discussionmentioning

confidence: 99%

Multi‐omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis

Challa,

Maras,

Nagpal

et al. 2024

Acad Dermatol Venereol

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BackgroundBacterial vaginosis (BV) is a common clinical manifestation of a perturbed vaginal ecology associated with adverse sexual and reproductive health outcomes if left untreated. The existing diagnostic modalities are either cumbersome or require skilled expertise, warranting alternate tests. Application of machine‐learning tools to heterogeneous and high‐dimensional multi‐omics datasets finds promising potential in data integration and may aid biomarker discovery.ObjectivesThe present study aimed to evaluate the potential of the microbiome and metabolome‐derived biomarkers in BV diagnosis. Interpretable machine‐learning algorithms were used to evaluate the utility of an integrated‐omics‐derived classification model.MethodsVaginal samples obtained from reproductive‐age group women with (n = 40) and without BV (n = 40) were subjected to 16S rRNA amplicon sequencing and LC–MS‐based metabolomics. The vaginal microbiome and metabolome were characterized, and machine‐learning analysis was performed to build a classification model using biomarkers with the highest diagnostic accuracy.ResultsMicrobiome‐based diagnostic model exhibited a ROC‐AUC (10‐fold CV) of 0.84 ± 0.21 and accuracy of 0.79 ± 0.18, and important features were Aerococcus spp., Mycoplasma hominis, Sneathia spp., Lactobacillus spp., Prevotella spp., Gardnerella spp. and Fannyhessea vaginae. The metabolome‐derived model displayed superior performance with a ROC‐AUC of 0.97 ± 0.07 and an accuracy of 0.92 ± 0.08. Beta‐leucine, methylimidazole acetaldehyde, dimethylethanolamine, L‐arginine and beta cortol were among key predictive metabolites for BV. A predictive model combining both microbial and metabolite features exhibited a high ROC‐AUC of 0.97 ± 0.07 and accuracy of 0.94 ± 0.08 with diagnostic performance only slightly superior to the metabolite‐based model.ConclusionApplication of machine‐learning tools to multi‐omics datasets aid biomarker discovery with high predictive performance. Metabolome‐derived classification models were observed to have superior diagnostic performance in predicting BV than microbiome‐based biomarkers.

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Dialister massiliensis sp. nov., a new bacterium isolated from the human gut

Cited by 6 publications

References 14 publications

Effects of ‘Healthy’ Fecal Microbiota Transplantation against the Deterioration of Depression in Fawn-Hooded Rats

Effects of ‘Healthy’ Fecal Microbiota Transplantation against the Deterioration of Depression in Fawn-Hooded Rats

Amelioration of depressive symptoms on Fawn-Hooded rats through the 'healthy' fecal microbiota transplantation

Multi‐omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis

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