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Laan, S. N. J.

Publications and source records attributed to Laan, S. N. J..

2 recordsLinked to original sources

Ecologically inspired assembly of a Bacillales synthetic community for lignin degradation

Lignin remains a major bottleneck in biomass valorization due to its heterogeneous and recalcitrant structure. Traditionally, lignin degradation has been developed using a single-microorganism or single-enzyme approach, with efforts focused on identifying ligninolytic activities of individual bacteria or fungi. Here, we establish a framework for designing lignin-degrading synthetic microbial communities (SynComs) by integrating top-down ecological filtering with bottom-up trait-based selection. This approach enables the selection of bacteria with ligninolytic capacity while retaining community members that form strong biofilms and contribute indirectly to overall community function. Proteomic profiling uncovered lignin-driven functional reprogramming of the SynCom, highlighting strain-specific enzymatic specializations that collectively enable lignin depolymerization. Our work highlights the potential of SynComs for lignin degradation and shows how rationally designed, functionally partitioned communities can enhance lignin conversion.

microbiology↗

Automated segmentation and quantitative analysis of organelle morphology, localization and content using CellProfiler

One of the most used and versatile methods to study number, dimensions, content and localization of secretory organelles is confocal microscopy analysis. However, considerable heterogeneity exists in the number, size and shape of secretory organelles that can be present in the cell. One thus needs to analyze large numbers of organelles for valid quantification. Properly evaluating these parameters requires an automated, unbiased method to process and quantitatively analyze microscopy data. Here, we describe two pipelines, run by CellProfiler software, called OrganelleProfiler and OrganelleContentProfiler. These pipelines were used on confocal images of endothelial colony forming cells (ECFC) which contain unique secretory organelles called Weibel-Palade bodies. Results show that the pipelines can quantify the cell count and size, and the organelle count, size, shape, relation to cells and nuclei, and distance to these objects. Furthermore, the pipeline is able to quantify secondary signals located in or on the organelle or in the cytoplasm. Cell profiler measurements were checked for validity using Fiji. To conclude, these pipelines provide a powerful, high-processing quantitative tool for analysis of cell and organelle characteristics. These pipelines are freely available and easily editable for use on different cell types or organelles.

cell biology↗