Elucidating regulation of polyhydroxyalkanoate metabolism in Ralstonia eutropha: Identification of transcriptional regulators from phasin and depolymerase genes.

Despite the ever-growing research interest in polyhydroxyalkanoates (PHAs) as green plastic alternatives, our understanding of the regulatory mechanisms governing PHA synthesis, storage, and degradation in the model organism Ralstonia eutropha remains limited. Given its importance for central carbon metabolism, PHA homeostasis is probably controlled by a complex network of transcriptional regulators. Understanding this fine-tuning is the key for developing improved PHA production strains thereby boosting the application of PHAs. We conducted promoter pull-down assays with crude protein extracts from R. eutropha Re2058/pCB113, followed by liquid chromatography with tandem mass spectrometry, to identify putative transcriptional regulators involved in the expression control of PHA metabolism, specifically targeting phasin phaP1 and depolymerase phaZ3 and phaZ5 genes. The impact on promoter activity was studied in vivo using ß-galactosidase assays and the most promising candidates were heterologously produced in Escherichia coli, and their interaction with the promoters investigated in vitro by electrophoretic mobility shift assays. We could show that R. eutropha DNA-binding xenobiotic response element-family-like protein H16_B1672, specifically binds the phaP1 promoter in vitro with a KD of 175 nM and represses gene expression from this promoter in vivo. Protein H16_B1672 also showed interaction with both depolymerase promoters in vivo and in vitro suggesting a broader role in the regulation of PHA metabolism. Furthermore, in vivo assays revealed that the H-NS-like DNA-binding protein H16_B0227 and the peptidyl-prolyl cis-trans isomerase PpiB, strongly repress gene expression from PphaP1 and PphaZ3, respectively. In summary, this study provides new insights into the regulation of PHA metabolism in R. eutropha, uncovering specific interactions of novel transcriptional regulators.

Protein complexes in cells by AI-assisted structural proteomics.

Accurately modeling the structures of proteins and their complexes using artificial intelligence is revolutionizing molecular biology. Experimental data enable a candidate-based approach to systematically model novel protein assemblies. Here, we use a combination of in-cell crosslinking mass spectrometry and co-fractionation mass spectrometry (CoFrac-MS) to identify protein-protein interactions in the model Gram-positive bacterium Bacillus subtilis. We show that crosslinking interactions prior to cell lysis reveals protein interactions that are often lost upon cell lysis. We predict the structures of these protein interactions and others in the SubtiWiki database with AlphaFold-Multimer and, after controlling for the false-positive rate of the predictions, we propose novel structural models of 153 dimeric and 14 trimeric protein assemblies. Crosslinking MS data independently validates the AlphaFold predictions and scoring. We report and validate novel interactors of central cellular machineries that include the ribosome, RNA polymerase, and pyruvate dehydrogenase, assigning function to several uncharacterized proteins. Our approach uncovers protein-protein interactions inside intact cells, provides structural insight into their interaction interfaces, and is applicable to genetically intractable organisms, including pathogenic bacteria.

Diversity of parvovirus 4-like viruses in humans, chimpanzees, and monkeys in hunter-prey relationships.

During 2010-2011, we investigated interspecies transmission of partetraviruses between predators (humans and chimpanzees) and their prey (colobus monkeys) in Côte d'Ivoire. Despite widespread infection in all species investigated, no interspecies transmission could be detected by PCR and genome analysis. All sequences identified formed species- or subspecies (chimpanzee)-specific clusters, which supports a co-evolution hypothesis.