Cell systems最新文献

Determining the specificity of adaptive immune receptors-B cell receptors (BCRs), their secreted form antibodies, and T cell receptors (TCRs)-is critical for understanding immune responses and advancing immunotherapy and drug discovery. Immune receptors exhibit extensive diversity in their variable domains, enabling them to interact with a plethora of antigens. Despite the significant progress made by AI tools such as AlphaFold in predicting protein structures, challenges remain in accurately modeling the structure and specificity of immune receptors, primarily due to the limited availability of high-quality crystal structures and the complexity of immune receptor-antigen interactions. In this perspective, we highlight recent advancements in sequence-based and structure-based data generation for immune receptors, which are crucial for training machine learning models that predict receptor specificity. We discuss the current bottlenecks and potential future directions in generating and utilizing high-dimensional datasets for predicting and designing the specificity of antibodies and TCRs.

Turing patterns are a key theoretical foundation for understanding organ development and organization. While they have been found to occur in natural systems, implementing new biological systems that form Turing patterns has remained challenging. To address this, Tica et al.¹ used synthetic genetic networks to engineer living cellular computers that successfully generate Turing patterns within growing bacterial populations.

Prostate cancer (PCA) exhibits high levels of intratumoral heterogeneity. In this study, we developed a mathematical model to study the growth and genetic evolution of PCA. We explored the possible evolutionary patterns and demonstrated that tumor architecture represents a major bottleneck for divergent clonal evolution. Early consecutive acquisition of strong genetic alterations serves as a proxy for the formation of aggressive tumors. A limited number of clonal hierarchy patterns were identified. A biopsy study of synthetic tumors shows complex spatial intermixing of clones and delineates the importance of biopsy extent. Deep whole-exome multiregional next-generation DNA sequencing of the primary tumors from five patients was performed to validate the results, supporting our main findings from mathematical modeling. In conclusion, our model provides qualitatively realistic predictions of PCA genomic evolution, closely aligned with the evidence available from patient samples. We share the code of the model for further studies. A record of this paper's transparent peer review process is included in the supplemental information.

Chromatin states play important roles in the maintenance of cell identities, yet their spatial patterns remain poorly characterized at the organism scale. We developed a systematic approach to analyzing spatial epigenomic data and then applied it to a recently published spatial-CUT&Tag dataset that was obtained from a mouse embryo. We identified a set of spatial genes whose H3K4me3 patterns delineate tissue boundaries. These genes are enriched with tissue-specific transcription factors, and their corresponding genomic loci are marked by broad H3K4me3 domains. Integrative analysis with H3K27me3 profiles showed coordinated spatial transitions across tissue boundaries, which is marked by the continuous shortening of H3K4me3 domains and expansion of H3K27me3 domains. Motif-based analysis identified transcription factors whose activities change significantly during such transitions. Taken together, our systematic analyses reveal a strong connection between the genomic and spatial variations of chromatin states. A record of this paper's transparent peer review process is included in the supplemental information.

Sexual reproduction in malaria parasites is essential for their transmission to mosquitoes and offers a divergent eukaryote model to understand the evolution of sex. Through a panel of genetic screens in Plasmodium berghei, we identify 348 sex and transmission-related genes and define roles for unstudied genes as putative targets for transmission-blocking interventions. The functional data provide a deeper understanding of female metabolic reprogramming, meiosis, and the axoneme. We identify a complex of a SUN domain protein (SUN1) and a putative allantoicase (ALLC1) that is essential for male fertility by linking the microtubule organizing center to the nuclear envelope and enabling mitotic spindle formation during male gametogenesis. Both proteins have orthologs in mouse testis, and the data raise the possibility of an ancient role for atypical SUN domain proteins in coupling the nucleus and axoneme. Altogether, our data provide an unbiased picture of the molecular processes that underpin malaria parasite transmission. A record of this paper's transparent peer review process is included in the supplemental information.

Bacteria employ diverse gene regulatory networks to survive stress, but deciphering the underlying logic of these complex networks has proved challenging. Here, we use time-resolved single-cell imaging to explore the functioning of the E. coli regulatory response to oxidative stress. We observe diverse gene expression dynamics within the network. However, by controlling for stress-induced growth-rate changes, we show that these patterns involve just three classes of regulation: downregulated genes, upregulated pulsatile genes, and gradually upregulated genes. The two upregulated classes are distinguished by differences in the binding of the transcription factor, OxyR, and appear to play distinct roles during stress protection. Pulsatile genes activate transiently in a few cells for initial protection of a group of cells, whereas gradually upregulated genes induce evenly, generating a lasting protection involving many cells. Our study shows how bacterial populations use simple regulatory principles to coordinate stress responses in space and time. A record of this paper's transparent peer review process is included in the supplemental information.

Danneskiold-Samsøe and coworkers¹ have developed an in silico screening pipeline based on AlphaFold2 for identifying single-pass transmembrane receptors for secreted peptides that play important roles in cell-cell signaling. Their approach can be used to deorphanize a diverse range of ligands. The overall strategy can be valuable in screening for weak and transient interactions.

Secreted proteins play crucial roles in paracrine and endocrine signaling; however, identifying ligand-receptor interactions remains challenging. Here, we benchmarked AlphaFold2 (AF2) as a screening approach to identify extracellular ligands to single-pass transmembrane receptors. Key to the approach is the optimization of AF2 input and output for screening ligands against receptors to predict the most probable ligand-receptor interactions. The predictions were performed on ligand-receptor pairs not used for AF2 training. We demonstrate high discriminatory power and a success rate of close to 90% for known ligand-receptor pairs and 50% for a diverse set of experimentally validated interactions. Further, we show that screen accuracy does not correlate linearly with prediction of ligand-receptor interaction. These results demonstrate a proof of concept of a rapid and accurate screening platform to predict high-confidence cell-surface receptors for a diverse set of ligands by structural binding prediction, with potentially wide applicability for the understanding of cell-cell communication.

While fecal microbiota transplantation (FMT) has been shown to be effective in reversing gut dysbiosis, we lack an understanding of the fundamental processes underlying microbial engraftment in the mammalian gut. Here, we explored a murine gut colonization model leveraging natural inter-individual variations in gut microbiomes to elucidate the spatiotemporal dynamics of FMT. We identified a natural "super-donor" consortium that robustly engrafts into diverse recipients and resists reciprocal colonization. Temporal profiling of the gut microbiome showed an ordered succession of rapid engraftment by early colonizers within 72 h, followed by a slower emergence of late colonizers over 15-30 days. Moreover, engraftment was localized to distinct compartments of the gastrointestinal tract in a species-specific manner. Spatial metagenomic characterization suggested engraftment was mediated by simultaneous transfer of spatially co-localizing species from the super-donor consortia. These results offer a mechanism of super-donor colonization by which nutritional niches are expanded in a spatiotemporally dependent manner. A record of this paper's transparent peer review process is included in the supplemental information.