| ORCID | https://orcid.org/0000-0001-7283-1768 |
| Homepage | https://porthmeus.github.io/ |
New review out: "Metabolic Modeling of Host–Microbe Interactions". In the article, we:
Outline strategies for coupling host and microbial genome scale metabolic models #GEM
Highlight successful applications revealing #HostMicrobiome cross-feeding
Discuss challenges (regulation, dynamics, model validation) and possible solutions
Outline fields which are worthwhile exploring from a #SystemsBiology perspective
We are looking for a #PhD student who applies #MetabolicModeling to explore metabolic #hostMicrobeInteraction in the #gutBrainAxis for #coginitiveDecline during #menopause. A special focus will be laid on the role of the #microbiome in the production/degradation of hormones and the consequences on the brain. Please share and recommend!
More infos here:
https://bsky.app/profile/kaletalab.bsky.social/post/3m2qlozorvs27
Ad for the vacancy is here:
https://www.uniklinikum-jena.de/menobrain/en/Recruitment+_+Open+Calls/DC+8+_+UKSH-p-42.html
1/4 🌍 We are looking for a passionate #PhD student in #Metabolic #Microbiome #Modeling in the Marie Skłodowska-Curie Doctoral Network MenoBrain. Join us at one of Europe’s microbiome research hubs and push the boundaries of microbiome science! @uni-kiel.de 🔗 https://www.uniklinikum-jena.de/menobrain/en/Recruitment+_+Open+Calls/DC+8+_+UKSH-p-42.html
Background Histone modifications are key epigenetic regulators of cell differentiation and have been intensively studied in many cell types and tissues. Nevertheless, we still lack a thorough understanding of how combinations of histone marks at the same genomic location, so-called chromatin states, are linked to gene expression, and how these states change in the process of differentiation. To receive insight into the epigenetic changes accompanying the differentiation along the chondrogenic lineage we analyzed two publicly available datasets representing (1) the early differentiation stages from embryonic stem cells into chondrogenic cells and (2) the direct differentiation of mature chondrocyte subtypes. Results We used ChromHMM to define chromatin states of 6 activating and repressive histone marks for each dataset and tracked the transitions between states that are associated with the progression of differentiation. As differentiation-associated state transitions are likely limited to a reduced set of genes, one challenge of such global analyses is the identification of these rare transitions within the large-scale data. To overcome this problem, we have developed a relativistic approach that quantitatively relates transitions of chromatin states on defined groups of tissue-specific genes to the background. In the early lineage, we found an increased transition rate into activating chromatin states on mesenchymal and chondrogenic genes while mature chondrocytes are mainly enriched in transition between activating states. Interestingly, we also detected a complex extension of the classical bivalent state (H3K4me3/H3K27me3) consisting of several activating promoter marks besides the repressive mark H3K27me3. Within the early lineage, mesenchymal and chondrogenic genes undergo transitions from this state into active promoter states, indicating that the initiation of gene expression utilizes this complex combination of activating and repressive marks. In contrast, at mature differentiation stages the inverse transition, the gain of H3K27me3 on active promoters, seems to be a critical parameter linked to the initiation of gene repression in the course of differentiation. Conclusions Our results emphasize the importance of a relative analysis of complex epigenetic data to identify chromatin state transitions associated with cell lineage progression. They further underline the importance of serial analysis of such transitions to uncover the diverse regulatory potential of distinct histone modifications like H3K27me3.
Most interestingly, the #microbialCommunities structure themselves to granules with inner anoxic regions - here the #photosynthesis can use H2S instead of H2O as electron acceptor - which is driven by an anoxic #sulfurCycle supported by the other anaerobic bacteria which produce the H2S to keep their place oxygen free.
Multiplets-droplets that capture more than one cell-are a known artefact in droplet-based single-cell RNA sequencing (scRNA-seq), yet their prevalence and impact remain underestimated. In this study, we assess the frequency of multiplets across diverse publicly available datasets and evaluate how well commonly used detection tools are able to identify them. Using cell hashing data to determine a lower bound of the true multiplet rate, we demonstrate that commonly used heuristic estimations systematically underestimate multiplet rates, and that existing tools-despite optimized parameters-detect only a small subset of cell-hashing multiplets. We further refine a Poisson-based model to estimate the true multiplet rate, revealing that actual rates can exceed heuristic predictions by more than twofold. Downstream analyses are significantly affected by multiplets: they are not confined to isolated clusters but are distributed throughout the transcriptional landscape, where they distort clustering and cell type annotation. Using both quantitative and qualitative approaches, we visualize these effects and show that cell-hashing-informed multiplet removal eliminates artefactual clusters and improves annotation clarity, whereas computationally detected multiplets fail to fully remove artefacts in the most common experimental contexts. Our findings confirm that multiplet contamination remains a pervasive and under-addressed issue in scRNA-seq analysis. Since most datasets lack multiplexing, researchers must often rely on heuristics and limited tools, leaving many multiplets unidentified. We advocate for more robust multiplet-detection strategies, including multimodal validation, to ensure more accurate and interpretable scRNA-seq results. ### Competing Interest Statement The authors have declared no competing interest. Deutsche Forschungsgemeinschaft, HO 1582/12
Daniel Hoffmann 🌼