Rhythmic gene expression can originate not only from the autonomous rhythm of clock genes but likely also from sleep-wake cycles. Jan and colleagues used a novel model-based approach to dissect these individual effects and found that both factors contribute to gene expression rhythms, varying in degree within and across tissues.
Analyses of gene-expression dynamics in research on circadian rhythms and sleep homeostasis often describe these two processes using separate models. Rhythmically expressed genes are, however, likely to be influenced by both processes. We implemented a driven, damped harmonic oscillator model to estimate the contribution of circadian- and sleep-wake-driven influences on gene expression. The model reliably captured a wide range of dynamics in cortex, liver, and blood transcriptomes taken from mice and humans under various experimental conditions. Sleep-wake-driven factors outweighed circadian factors in driving gene expression in the cortex, whereas the opposite was observed in the liver and blood. Because of tissue- and gene-specific responses, sleep deprivation led to a long-lasting intra- and inter-tissue desynchronization. The model showed that recovery sleep contributed to these long-lasting changes. The results demonstrate that the analyses of the daily rhythms in gene expression must take the complex interactions between circadian and sleep-wake influences into account. A record of this paper’s transparent peer review process is included in the supplemental information.
As words can have multiple meanings that depend on sentence context, genes can have various functions that depend on the surrounding biological system. This pleiotropic nature of gene function is limited by ontologies, which annotate gene functions without considering biological contexts. We contend that the gene function problem in genetics may be informed by recent technological leaps in natural language processing, in which representations of word semantics can be automatically learned from diverse language contexts. In contrast to efforts to model semantics as “is-a” relationships in the 1990s, modern distributional semantics represents words as vectors in a learned semantic space and fuels current advances in transformer-based models such as large language models and generative pre-trained transformers. A similar shift in thinking of gene functions as distributions over cellular contexts may enable a similar breakthrough in data-driven learning from large biological datasets to inform gene function.
The placenta is a selective maternal-fetal barrier that provides nourishment and protection from infections. However, certain pathogens can attach to and even cross the placenta, causing pregnancy complications with potential lifelong impacts on the child’s health. Here, we profiled at the single-cell level the placental responses to three pathogens associated with intrauterine complications—Plasmodium falciparum, Listeria monocytogenes, and Toxoplasma gondii. We found that upon exposure to the pathogens, all placental lineages trigger inflammatory responses that may compromise placental function. Additionally, we characterized the responses of fetal macrophages known as Hofbauer cells (HBCs) to each pathogen and propose that they are the probable niche for T. gondii. Finally, we revealed how P. falciparum adapts to the placental microenvironment by modulating protein export into the host erythrocyte and nutrient uptake pathways. Altogether, we have defined the cellular networks and signaling pathways mediating acute placental inflammatory responses that could contribute to pregnancy complications.
BMP signaling is essential for mammalian gastrulation, as it initiates a cascade of signals that control self-organized patterning. As development is highly dynamic, it is crucial to understand how time-dependent combinatorial signaling affects cellular differentiation. Here, we show that BMP signaling duration is a crucial control parameter that determines cell fates upon the exit from pluripotency through its interplay with the induced secondary signal WNT. BMP signaling directly converts cells from pluripotent to extraembryonic fates while simultaneously upregulating Wnt signaling, which promotes primitive streak and mesodermal specification. Using live-cell imaging of signaling and cell fate reporters together with a simple mathematical model, we show that this circuit produces a temporal morphogen effect where, once BMP signal duration is above a threshold for differentiation, intermediate and long pulses of BMP signaling produce specification of mesoderm and extraembryonic fates, respectively. Our results provide a systems-level picture of how these signaling pathways control the landscape of early human development.
We have asked Ukrainian scientists how they have been able to persist in pursuing their research since the beginning of the full-scale invasion of Ukraine by the Russian Federation in February of 2022. We thank the scientists who were willing to share their thoughts and experiences; the views expressed are those of the contributors alone.
The cellular DNA damage response pathway can have vastly different outcomes depending on the source of its activation. Justice and colleagues apply phosphoproteomics to uncover a divergence in DNA-PK and ATM kinase activities in the contexts of DNA damage and DNA virus infection.
One snapshot of the peer review process for “A map of signaling responses in the human airway epithelium” (McCauley et al., 2024).1