bioRxiv Science⌕ Search

Biology subjects

Dahlgren, K.

Publications and source records attributed to Dahlgren, K..

2 recordsLinked to original sources

Molecular insights into phycobilisome assembly pathway reveal crystalline bodies in cyanobacteria

In oxygenic photosynthetic organisms, light energy is converted to chemical energy to drive CO2 fixation reactions and sustain life on Earth. Cyanobacteria contain phycobilisome (PBS) complexes that play critical roles in light harvesting and directing light energy to the photosystem I and II reaction centers. The proper assembly of PBS components is an intricate process that is required for their activity and association with photosystem I and II. To understand the complex mechanisms regulating the PBS assembly, we knocked out the terminal emitter apcE, which forms the structural scaffold for the PBS core. ApcE knockout led to growth and pigment defects, including elevated levels of photosystem II and abnormal emission spectra. Light microscopy experiments revealed the accumulation of highly fluorescent puncta localized to the pole of apcE knockout cells. Further investigation using electron cryo-tomography identified highly repetitive crystalline arrays of densely packed PBS cylinders. Together, these data indicate that cyanobacteria may accumulate PBS components in the form of highly organized crystalline bodies as intermediates during PBS assembly.

microbiology↗

Blastocoel fluid RNA predicts pregnancy outcome in assisted reproduction

Nearly one in eight couples are affected by infertility, with many relying on assisted reproductive technologies (ART) to conceive. However, selecting the highest-quality embryo in ART remains a major challenge, as current assessment methods are often subjective, or invasive, and lack precision. Here, we introduce a novel strategy that analyses embryo-derived polyadenylated RNA in blastocoel fluid to more accurately predict pregnancy outcomes. Elevated RNA levels were strongly associated with implantation failure, particularly in embryos from women over the age of 34. Our predictive model developed using our sample cohort, incorporating both RNA and maternal age, demonstrated exceptional performance, achieving 76% accuracy in the training set and 73% in independent validation in predicting implantation outcome-- highlighting a promising advancement in embryo selection and ART success.

molecular biology↗