MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context

Koblitz, Julia; Schomburg, Dietmar; Neumann‐Schaal, Meina

doi:10.12688/f1000research.23427.2

Cited by 8 publications

(5 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the sparsity of the points in the PCA space suggests that samples are metabolically diverse. To visualise the conclusions from the previous correlation/PCA analysis about how TCA metabolites have a similar landscape, and why the opposite trend is found in other metabolite categories, we embedded the metabolite surfaces into a simplified pathway diagram for anabolism in Bacillus subtilis (Figure S5) [63]. These are the predictions of the machine learning model for the abundance of each metabolite across the carbon and nitrogen concentration ranges.…”

Section: Resultsmentioning

confidence: 99%

“…The copyright holder for this preprint this version posted January 25, 2024. ; https://doi.org/10.1101/2024.01.24.576661 doi: bioRxiv preprint opposite trend is found in other metabolite categories, we embedded the metabolite surfaces into a simplified pathway diagram for anabolism in Bacillus subtilis (Figure S5) [63]. These are the predictions of the machine learning model for the abundance of each metabolite across the carbon and nitrogen concentration ranges.…”

Section: Active Learning Of the Surfactin C Yield Landscapementioning

confidence: 99%

See 1 more Smart Citation

Optimisation of surfactin yield inBacillususing active learning and high-throughput mass spectrometry

Albornoz,

Oyarzún,

Burgess

2024

Preprint

View full text Add to dashboard Cite

Integration of machine learning and high throughput measurements are essential to drive the next generation of the design-build-test-learn (DBTL) cycle in synthetic biology. Here, we report the use of active learning in combination with metabolomics for optimising production of surfactin, a complex lipopeptide resulting from a non-ribosomal assembly pathway. We designed a media optimisation algorithm that iteratively learns the yield landscape and steers the media composition toward maximal production. The algorithm led to a 160% yield increase after three DBTL runs as compared to an M9 baseline. Metabolomics data helped to elucidate the underpinning biochemistry for yield improvement and revealed Pareto-like trade-offs in production of other lipopeptides from related pathways. We found positive associations between organic acids and surfactin, suggesting a key role of central carbon metabolism, as well as system-wide anisotropies in how metabolism reacts to shifts in carbon and nitrogen levels. Our framework offers a novel data-driven approach to improve yield of biological products with complex synthesis pathways that are not amenable to traditional yield optimisation strategies.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Active Learning Of the Surfactin C Yield Landscapementioning

confidence: 99%

Optimisation of surfactin yield inBacillususing active learning and high-throughput mass spectrometry

Albornoz,

Oyarzún,

Burgess

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The results of differential gene expression from DESeq2 were mapped to the archaeal cluster of orthologous genes (arCOGs) and then manually revised [ 59 ]. Figures were constructed using standard graphics editing software based on MetaboMAPS [ 60 ].…”

Section: Methodsmentioning

confidence: 99%

Membrane Adaptations and Cellular Responses of Sulfolobus acidocaldarius to the Allylamine Terbinafine

Rao

Kok

Driessen

2023

IJMS

View full text Add to dashboard Cite

Cellular membranes are essential for compartmentalization, maintenance of permeability, and fluidity in all three domains of life. Archaea belong to the third domain of life and have a distinct phospholipid composition. Membrane lipids of archaea are ether-linked molecules, specifically bilayer-forming dialkyl glycerol diethers (DGDs) and monolayer-forming glycerol dialkyl glycerol tetraethers (GDGTs). The antifungal allylamine terbinafine has been proposed as an inhibitor of GDGT biosynthesis in archaea based on radiolabel incorporation studies. The exact target(s) and mechanism of action of terbinafine in archaea remain elusive. Sulfolobus acidocaldarius is a strictly aerobic crenarchaeon thriving in a thermoacidophilic environment, and its membrane is dominated by GDGTs. Here, we comprehensively analyzed the lipidome and transcriptome of S. acidocaldarius in the presence of terbinafine. Depletion of GDGTs and the accompanying accumulation of DGDs upon treatment with terbinafine were growth phase-dependent. Additionally, a major shift in the saturation of caldariellaquinones was observed, which resulted in the accumulation of unsaturated molecules. Transcriptomic data indicated that terbinafine has a multitude of effects, including significant differential expression of genes in the respiratory complex, motility, cell envelope, fatty acid metabolism, and GDGT cyclization. Combined, these findings suggest that the response of S. acidocaldarius to terbinafine inhibition involves respiratory stress and the differential expression of genes involved in isoprenoid biosynthesis and saturation.

show abstract

“…Metabolomics data and transcriptomics data were visualized using MetaboMAPS [75]. Pathway was condensed into a custom gure.…”

Section: Sanger Sequencingmentioning

confidence: 99%

Early-life exposure to a potent Aryl hydrocarbon receptor ligand results in persistent changes to the microbiota and host glucose homeostasis

Tian

Rimal

Bisanz

et al. 2023

Preprint

View full text Add to dashboard Cite

Background Exposure to persistent organic pollutants (POPs) and gastrointestinal microbial disruption positively corelate with a predisposition to factors including obesity, metabolic syndrome, and type 2 diabetes; however, it is unclear if and how the microbiome contributes to this relationship. Results Here, we show that early-life exposure to a potent aryl hydrocarbon receptor (AHR) agonist in mice resulted in persistent microbiota disruptions associated with impaired glucose homeostasis later in life. 2,3,7,8-tetrachlorodibenzofuran (TCDF)-exposed mice exhibited a profound disruption in the gut microbiome characterized by decreased abundances of Akkermansia muciniphila (A. muciniphila), decreased levels of cecal short chain fatty acids (SCFAs) and indole-3-lactic acid (ILA), and reduction of gut hormones GLP-1 and PYY. Importantly, microbial and metabolic phenotypes associated with early-life POP exposure were transferable to germ-free recipients in the absence of POP carry-over. Consistent with these in vivo studies, we reveal a direct, AHR-independent, POP-microbiota interaction that significantly affected the growth, physiology, gene expression, and metabolic activity of A. muciniphila, resulting in suppressed activity along the ILA pathway. Conclusions These data point to a complex effect of POPs on the host and microbiota providing strong evidence that early-life, short-term, and self-limiting POP exposure can adversely impact the microbiome which persists into later life with associated health implications.

show abstract

MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context

Cited by 8 publications

References 9 publications

Optimisation of surfactin yield inBacillususing active learning and high-throughput mass spectrometry

Optimisation of surfactin yield inBacillususing active learning and high-throughput mass spectrometry

Membrane Adaptations and Cellular Responses of Sulfolobus acidocaldarius to the Allylamine Terbinafine

Early-life exposure to a potent Aryl hydrocarbon receptor ligand results in persistent changes to the microbiota and host glucose homeostasis

Contact Info

Product

Resources

About