Cell systems最新文献

Complex karyotype changes are widespread in cancer genomes. A major gap in cancer genome characterization is the resolution of rearranged chromosomes with chromosome-length continuity. Here, we describe a two-tiered approach to determine the segmental composition of rearranged chromosomes with haplotype resolution. First, we present refLinker, a bioinformatic method for robust determination of chromosomal haplotypes using cancer Hi-C data. By contrast with existing methods, refLinker is insensitive to the presence of large-scale DNA deletions, duplications, and high-level amplification in cancer genomes. Second, we demonstrate a computational strategy to determine the segmental structure of rearranged chromosomes using haplotype-specific Hi-C contacts. We apply these methods to breast cancer genomes and provide direct evidence for long-range transcriptional changes associated with rearrangements of the inactive X chromosome. Together, these results highlight refLinker's broad utility for studying the functional consequences of chromosomal rearrangements.

Two-component systems (TCSs) are ubiquitous multi-step signal sensing systems in prokaryotes and are promising platforms for building cellular sensors. However, their programmability remains underexplored, limiting broader applications in synthetic biology. Here, we refactor TCSs to systematically elucidate the functional properties of response regulator (RR) and histidine kinase (HK) as the concentration-dependent activator and inhibitor for TCS sensor output, respectively. By decoupling HK expression from native feedback circuitry, we engineer ultrasensitive TCS sensors with tunable detection thresholds. By leveraging RR as a transducer, we couple one-component system (OCS) and TCS to create a synergistic sensing system (SSS) characterized by both a low detection limit and a high dynamic range. We further show that RR alone serves as a biological-low noise amplifier (LNA), substantially upgrading performance of diverse genetically encoded biosensors. Our study demonstrates TCS's high plasticity and programmability for customizing gene expression regulation in synthetic circuits, providing modular toolkits for biosensor optimization. A record of this paper's transparent peer review process is included in the supplemental information.

Intercellular signaling in bacteria is often mediated by small molecules secreted by cells. These small molecules disperse via diffusion, which limits the speed and spatial extent of information transfer in spatially extended systems. Theory shows that a secondary signal and feedback circuits can speed up the flow of information and allow it to travel further. Here, we construct and test several synthetic circuits in Escherichia coli to determine to what extent a secondary signal and feedback can improve signal propagation in bacterial systems. We find that positive feedback-regulated secondary signals propagate further and faster than diffusion-limited signals. Additionally, the speed at which the signal propagates can accelerate in time, provided the density of the cells within the system increases. These findings provide the foundation for creating fast, long-range signal propagation circuits in spatially extended bacterial systems.

The epigenetic landscape and tumor microenvironment (TME) interactions of non-functioning pituitary adenomas (NFPAs), benign tumors with high morbidity and recurrence rates, are not well characterized. We completed single-nucleus (sn) multiomics assays on 4 gonadotrope NFPAs (34,819 cells) and 11 non-diseased postmortem control pituitaries (51,535 cells), finding decreased proportions of tumor-associated endothelial cells and pericytes and increased proportions of macrophages. We identified bidirectional tumor-macrophage crosstalk comprising nine ligand-receptor interactions and experimentally validated the macrophage-initiated SFRP1-FZD6 interaction, whose predicted target genes CCND1, CDK6, SGK1, and TGFBR2 were linked to tumorigenesis. We uncovered coordinated gene expression and chromatin accessibility programs, which distinguished adenoma cells from gonadotropes. Integrated transcriptome-chromatin modeling revealed gene regulatory circuits (GRCs) that showed altered activity in adenoma cells and were regulated by transcription factors (TFs), including PBX3 and MEF2C. Our study provides insight into the altered epigenetic gene control landscape and TME processes of the NFPA tumor phenotype. Our data are freely available at https://rstudio-connect.hpc.mssm.edu/nfpa_browser/.

The ability to sequence proteins without reliance on a genomic template defines a critical frontier in proteomics. This approach, known as de novo protein sequencing, is essential for applications in antibody sequencing, microbiome proteomics, and antigen discovery, which require accurate reconstruction of target sequences. To advance this field, we here explore two hyperthermoacidic archaeal (HTA) proteases for de novo antibody sequencing, benchmarking them against trypsin and chymotrypsin. Each HTA-protease generated about five times more unique peptide reads than trypsin or chymotrypsin, providing high redundancy across all complementarity-determining regions. Combined with EAciD fragmentation on a ZenoTOF, this methodology enabled complete, unambiguous antibody sequencing. De novo analysis showed much higher alignment scores and reduced the sequence errors by using the HTA-generated data. With short digestion times, minimal sample cleanup, and analysis in just a single liquid chromatography-mass spectrometry (LC-MS/MS) run, this streamlined single-protease approach delivers a scalable and efficient strategy for de novo protein sequencing across diverse applications. A record of this paper's transparent peer review process is included in the supplemental information.

Metabolite concentration changes can have broad consequences on the function and robustness of metabolic networks. Here, we measured the metabolome response of 1,515 CRISPR interference (CRISPRi) E. coli strains targeting all genes in the iML1515 metabolic model. Metabolites that are hardly measurable in wild-type E. coli accumulated in specific CRISPRi strains, indicating that they are normally maintained at low levels. We confirmed metabolite accumulation using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and generated putative reference spectra for 102 metabolites for which no MS² data had previously been available. We show that minimal metabolite levels are beneficial because they (1) enable substrate level regulation of enzyme activity, (2) prevent competitive inhibition, and (3) suppress side reactions. However, minimal metabolite pools also limit flux through engineered pathways. For example, low levels of farnesyl diphosphate (frdp) constrained a synthetic carotenoid pathway, and we show that the knockdown of octaprenyl diphosphate synthase (IspB) increased frdp levels and carotenoid production. A record of this paper's transparent peer review process is included in the supplemental information.

Mutant phenotypes often vary across genetically distinct individuals. To identify the causes of such genetic background effects, we studied differences in gene essentiality across 18 genetically diverse natural yeast strains. We identified 39 genes that were essential in the laboratory reference strain but not in at least one other genetic background, and we mapped and validated the genetic variants that were responsible for the differences in gene essentiality. These variants typically occurred in single modifier genes that tended to differ between genetic backgrounds. The affected genes often indirectly compensated for the loss of the essential gene and identified naturally occurring evolutionary trajectories. Overall, our results highlight the prevalence of changes in gene essentiality in natural populations, as well as the underlying mechanisms. A thorough understanding of the causes of genetic background effects is crucial for the interpretation of genotype-to-phenotype relationships, including those associated with human disease.

Cell-to-cell heterogeneity in infection outcome is a general feature of most viruses, but the underlying mechanisms are poorly understood. Here, we developed a live-cell single-molecule imaging technology to visualize infection by unmodified influenza A viruses (IAVs) with unprecedented resolution. Using this approach, we generated a detailed kinetic map of IAV infection, which identified viral ribonucleoprotein (vRNP) replication, nuclear export, and virion budding as important sources of heterogeneity. Mechanistically, we show that infection heterogeneity is caused by differential viral gene expression signatures, resulting from widespread transcriptional defects and loss of viral genome segments. For example, loss of NS, but surprisingly not polymerase subunits, severely delays replication onset, and loss of M and NS, but not HA, underlies vRNP nuclear export defects. In summary, our work identifies the origin and consequences of infection heterogeneity and provides a broadly applicable technology that allows high-resolution phenotyping of unmodified IAVs and other negative-strand RNA viruses.

In aged humans and mice, hypobranched glycogen aggregates, known as polyglucosan bodies (PGBs), accumulate in hippocampal astrocytes. While PGBs are linked to cognitive decline in neurological diseases, they remain largely unstudied in the context of typical aging. We show that PGBs arise in autophagy-dysregulated astrocytes in the aged hippocampus, with substantial variation among 32 inbred BXD mouse strains. Genetic mapping through quantitative trait locus analysis identified a major locus (Pgb1) that modulates hippocampal PGB burden. Extensive transcriptomic and proteomic datasets were produced for the aged hippocampus of the BXD family to investigate the mechanism by which the Pgb1 locus modulates PGB burden. We identified that Pgb1 contains allelic Smarcal1 and Usp37 variants and influences PGB burden through trans-regulation of mRNA and protein expression levels, including abundance of glycogen-mobilizing factor PYGB. Furthermore, comprehensive phenome-wide association scans, transcriptomic analyses, and direct behavioral testing demonstrated that cognition remains intact despite age-related PGB burden. A record of this paper's transparent peer review process is included in the supplemental information.

Unlike genome editing, RNA editing offers the ability to transiently alter cells with minimal risk from off-target effects. While exon-skipping technologies can influence splice site selection, many desired perturbations to the transcriptome require replacement or addition of exogenous exons to target mRNAs, such as replacing disease-causing exons, repairing truncated proteins, or engineering protein fusions. Here, we report the development of RNA-guided trans-splicing with Cas editor (RESPLICE). RESPLICE uses two orthogonal RNA-targeting CRISPR effectors to co-localize a trans-splicing pre-mRNA and to inhibit the cis-splicing reaction, respectively. We demonstrate efficient, specific, and programmable trans-splicing of RNA cargo (up to 2.1 kb) into 11 endogenous transcripts across 3 cell types, achieving up to 45% trans-splicing efficiency in bulk or 90% when sorting for high effector expression. Our results present RESPLICE as a mode of RNA editing that could provide fine-tuned and transient control of cellular programs.