Meiotic development initiation in the fungus Podospora anserina requires the peroxisome receptor export machinery.

Peroxisomes are versatile organelles essential for diverse developmental processes. One such process is the meiotic development of Podospora anserina. In this fungus, absence of the docking peroxin PEX13, the RING-finger complex peroxins, or the PTS2 co-receptor PEX20 blocks sexual development before meiocyte formation. However, this defect is not seen in the absence of the receptors PEX5 and PEX7, or of the docking peroxins PEX14 and PEX14/17. Here we describe the function of the remaining uncharacterized P. anserina peroxins predictably involved in peroxisome matrix protein import. We show that PEX8, as well as the peroxins potentially mediating receptor monoubiquitination (PEX4 and PEX22) and membrane dislocation (PEX1, PEX6 and PEX26) are indeed implicated in peroxisome matrix protein import in this fungus. However, we observed that elimination of PEX4 and PEX22 affects to different extent the import of distinct PEX5 cargoes, suggesting differential ubiquitination-complex requirements for the import of distinct proteins. In addition, we found that elimination of PEX1, PEX6 or PEX26 results in loss of peroxisomes, suggesting that these peroxins restrain peroxisome removal in specific physiological conditions. Finally, we demonstrate that all analyzed peroxins are required for meiocyte formation, and that PEX20 function in this process depends on its potential monoubiquitination target cysteine. Our results suggest that meiotic induction relies on a peroxisome import pathway, which is not dependent on PEX5 or PEX7 but that is driven by an additional cycling receptor. These findings uncover a collection of peroxins implicated in modulating peroxisome activity to facilitate a critical developmental cell fate decision.

Metagenomics Bioinformatic Pipeline.

Microbial communities' taxonomic and functional diversity has been broadly studied since sequencing technologies enabled faster and cheaper data obtainment. Nevertheless, the programming skills needed and the amount of software available may be overwhelming to someone trying to analyze these data. Here, we present a comprehensive and straightforward pipeline that takes shotgun metagenomics data through the needed steps to obtain valuable results. The raw data goes through a quality control process, metagenomic assembly, binning (the obtention of single genomes from a metagenome), taxonomic assignment, and taxonomic diversity analysis and visualization.