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Fu, E.

Publications and source records attributed to Fu, E..

5 recordsLinked to original sources

Full-length transcriptomics and proteomics reveal how genome minimization reshapes gene expression in synthetic bacteria

JCVI-syn1.0 (Syn1.0) and JCVI-syn3A (Syn3A), genetically synthetic and genome-reduced versions of the naturally occurring bacterium Mycoplasma mycoides, are landmark platforms for defining the gene set required for life, yet how their genomes are expressed at the RNA level remains uncharacterized. We combined full-length PacBio and native long-read RNA sequencing with short-read quantification and complementary proteomics to map transcription, RNA processing, and protein abundance in both cells. In Syn1.0, full-length sequencing resolved 459 operons encompassing 911 genes, revealing pervasive RNA processing with a strong 3' bias. Analysis of the division and cell-wall cluster showed how transcriptional context explained the restoration of genes required for normal cell division in Syn3A. Most antisense and intergenic transcription in Syn1.0 reflected low-level transcriptional noise arising from inherited mis-annotation, read-through, and synthetic sequences. Much of that transcription was lost in Syn3A after genome minimization. Reducing the genome unexpectedly altered the expression of several retained genes by deleting promoters, most prominently reducing expression of the nucleoid protein HupA and central-carbon enzymes. Meanwhile, one third of the coding mRNA pool was allocated to a single 21-gene ribosomal-protein operon, while several other ribosomal proteins had reduced transcript abundance, which possibly led to imbalanced ribosome assembly. Expression of RNA polymerase and central-carbon metabolism declined at both mRNA and protein levels whereas RNase Y degradosome abundance increased. These shifts in the synthetic evolution of Syn3A suggest plausible mechanisms for its reduced chromosome contacts and slower growth. Together, these results show that genome minimization alters not only gene content but also the transcriptional context and resource allocation of retained genes. The analysis and visualization that are shared via Jupyter Notebook provide the RNA-level foundation for whole-cell modeling of the minimal cell.

synthetic biology↗

COTree: A Statistical Framework for Deciphering Cell-Resolved Multi-Omics Trajectories

Recent advances in whole-cell modeling enable the computational tracking of the temporal evolution of thousands of molecular species across genomic, transcriptomic, proteomic, and metabolomic layers. These models provide a complementary perspective for studying cellular dynamics, offering continuous, system-wide observations that are difficult to obtain from experimental technologies, which are often destructive and yield only static measurements from limited modalities. While whole-cell models generate multi-omic simulation trajectories with high temporal resolution, analyzing and interpreting such complex data remains a major challenge that limits their potential to elucidate cellular dynamics. To address this challenge, we propose COTree, a statistical framework that learns integrated multi-omic representations and constructs a trajectory principal tree to summarize cellular progression patterns. COTree enables a broad range of downstream analyses, including cell classification, fate prediction, developmental time detection, and driver species identification, that provide new insights into how cells develop and differentiate. To demonstrate its practical utility, we apply COTree to a multi-omic trajectory dataset generated from the whole-cell model of JCVI-Syn3A, revealing cell types, characterizing long-term cellular dynamics, and identifying key driver species associated with cell death and replication.

bioinformatics↗

Assembly of Macromolecular Complexes in the Whole-Cell Model of a Minimal Cell

Macromolecular complexes in the genetically minimized bacterium, JCVI-syn3A, support gene expression (RNA polymerase, ribosome, degradosome), metabolism (ABC transporters, ATP synthase) and chromosome dynamics. In this work, we further incorporate the assembly of 21 unique macromolecular complexes into the existing whole-cell kinetic model of Syn3A. The synthesis and translocation of protein subunits in membrane complexes occur through distinct pathways. A range of 2D association rates for membrane complexes were considered to guarantee a high yield of assembly given the existing time scales of gene expression. By alleviating the undesired kinetically trapped intermediates in ATP synthase assembly, the efficiency was improved. The assembly of RNA polymerase, ribosome, and degradosome influence the speed and efficiency of protein synthesis. Collectively, this model predicted time-dependent cellular behaviors consistent with experiments. A machine learning analysis of the time-dependent metabolomics and metabolic fluxes highlighted the effect of introducing complex assembly into our whole-cell model.

biophysics↗

Bringing the Genetically Minimal Cell to Life on a Computer in 4D

We present a whole-cell spatial and kinetic model for the 100 minute cell cycle of the genetically minimal bacterium, JCVI-syn3A. This is the first simulation of a complete cell cycle in 4D including all genetic information processes, metabolic networks, growth, and cell division. Integrating hybrid computational methods, dynamics of the morphological transformations were achieved. Growth is driven by synthesis of lipids and membrane proteins and constrained by new fluorescence imaging data. Chromosome replication and segregation is controlled by essential SMC and topoisomerase proteins in Brownian dynamics simulations with replication rates responding to dNTP pools from metabolism. The model captures the origin to terminus ratio measured in our DNA sequencing and recovers other experimental measurements like doubling time, mRNA half-lives, protein distributions, and ribosome counts. Because of stochasticity, each replicate cell is unique. Not only do we predict average behavior for partitioning to daughter cells, we predict the heterogeneity among them.

biophysics↗

CK2 directly controls CARD9 protein homeostasis

CARD9 is an attractive target for therapeutic intervention because the human genetic data provides strong evidence for the causal role of CARD9 in both protection and susceptibility to autoimmune disease. Expression quantitative trait loci (eQTLs) link higher CARD9 expression to increased disease risk and lower CARD9 expression to protection. Additionally, a rare allele variant leading to a C-terminal truncation of CARD9 (CARD9{Delta}11) and subsequent loss-of-function is also protective for inflammatory bowel disease (IBD). The mechanism of CARD9-driven inflammation through scaffold assembly with BCL10 and MALT1 (CBM complex) suggests a durable inflammatory signal driven by increasing levels of CARD9. Therefore, CARD9 depletion is a desired therapeutic strategy for drug discovery, yet a difficult one due to the nature of CARD9 as an adaptor protein target and the limited number of chemical tools available to engage it. Here, we uncover through a protein homeostasis screen that casein kinase 2 (CK2/CSNK2) inhibition leads to cellular CARD9 depletion. Following up with arrayed CRISPR screening, we identify key casein kinase isoforms/subunits responsible for CARD9 depletion. We find that CK2 directly binds to CARD9 and phosphorylates S424/S425 as well as S483/S484. Orthosteric CK2 inhibition prevents CK2 binding to CARD9 and leads to CARD9 destabilization. We show that the interaction between CK2 and CARD9{Delta}11 is significantly attenuated and not sensitive to CK2-mediated protein stabilization. The CK2-driven CARD9 depletion mechanism is preserved outside of immortalized cell lines and conserved between primary, differentiated mouse and human dendritic cells. Finally, we demonstrate therapeutic proof of concept in vivo using CK2 inhibition to deplete CARD9 in murine whole blood, peritoneum, and colon. Our study expands the scope of cellular consequences dealt by kinase inhibition, offers an unconventional approach for engaging a therapeutically intractable target, and identifies a novel mechanism that could contribute to disease protection conferred by the CARD9{Delta}11 allele.

immunology↗