Biology subjects

Mehta, A. P.

Publications and source records attributed to Mehta, A. P..

4 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

Spatiotemporal 4D Whole-cell Modeling of a Minimal Autotroph Reveals Central Carbon Metabolism Regulated Locally by Protein Megacomplexes via Post-translational Modifications under Light Disturbance

Photosynthetic microorganisms rely on multiple pathways in central carbon metabolism to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes spanning disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. To address this complexity beyond genome-based inference and traditional modeling, we develop a whole-cell four-dimensional (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial organization of enzymatic and molecular processes in central carbon metabolism under light perturbation. We employ a perturbation-based research design to experimentally generate time-series, multi-omics measurements that provide molecular descriptors and cryo-ET images as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulating the structural assembly of a protein megacomplex, the "dark complex," modulate metabolic flux at a conserved regulatory node of the Calvin-Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates that post-translational regulation not only buffers transcriptional noise and diffusion-driven fluctuations but also stabilizes phenotypic outcomes, underscoring the importance of spatial heterogeneity in phenotypic robustness. This ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and central carbon metabolism addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4. Significance StatementThis work advances 4D whole-cell modeling by presenting the first spatiotemporal simulation of a photosynthetic autotroph using the Lattice Microbes platform. Using Prochlorococcus marinus MED4, we show that subcellular spatial organization of organelles, diffusion constraints, and redox regulation collectively shape central carbon metabolism across orders of magnitude in space and time. Through a perturbation-based strategy that generates multi-omics data sets over time, we construct and validate a spatially and temporally resolved model of MED4, constrained by high-resolution (10 nm) cryo-electron tomography. Our results highlight the importance of localized biochemical reactions and redox-dependent post-translational modification of enzymes in regulating carbon fixation in a noisy environment under light disturbance. This study establishes a spatiotemporal, whole-cell physiology modeling framework as a transformative tool for uncovering multiscale regulatory responses to environmental gradients.

systems biology↗

bioRxiv2025

Unraveling the Transcriptional Landscape within a Minimized Bacterium via Comparative Analysis

Stochastic nature of gene expression leads to the complex formation of the bacterial transcriptome and proteome. In contrast to typical transcriptome studies, we employ a near wild-type, Syn1.0, of the naturally genome-reduced Mycoplasmas, and the dramatically further genome-reduced JCVI-syn3A thus avoiding additional contributions from many non-essential cellular functions. To aid in profiling the transcriptional landscape within these bacteria, we present a bioinformatic analysis of the genetic sequence motifs implicated in modulating the stochastic gene expression events, coupled with genome-wide short-read (Illumina) and long-read (Oxford Nanopore Technologies and Pacfic Biosciences) RNA sequencing. The bioinformatic analysis coupled with information from structural studies assigns strengths of the Shine-Dalgarno signatures and identifies both transcription initiation and termination sites, leading to predictions of RNA isoforms in Syn1.0 (and related organisms). The long-read and short-read RNA sequencing characterized the predicted transcriptional activity, and the long-read methods provide direct insight into the RNA isoform complexity within Syn1.0. Comparison of the RNA sequencing results with that of the bioinformatic analysis highlights the inability of bioinformatics alone to capture the results of bacterial transcription without including effects of RNA degradation. This study emphasizes the need for comparative analysis and potential dangers of genome reduction, exemplified through the discovery of altered gene expression patterns of JCVI-syn1.0 and JCVI-syn3A, achieved via the union of our transcriptome study with their proteomics data. Analysis of the transcriptomics data sets through a Jupyter notebook allows any genomic region to be easily examined. Table of Content Image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/681674v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@78a9e0org.highwire.dtl.DTLVardef@1d8c9fcorg.highwire.dtl.DTLVardef@1b4e129org.highwire.dtl.DTLVardef@2a8c3f_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Virus-free continuous directed evolution in human cells using somatic hypermutation

The B cells of the human immune system have evolved somatic hypermutation (SHM) mechanisms that introduce mutations at the immunoglobulin genomic loci at a significantly higher frequency than the rest of the genome thereby allowing them to evolve antibody sequences without compromising fitness due to genome-wide mutations. Inspired by these observations, here we developed a continuous directed evolution platform in human B cell lines (CODE-HB) that repurposes the SHM mechanisms to a stable, non-immunoglobulin genomic locus of the human B cell lines to continuously evolve cytosolic and surface displayed proteins with a broad mutational spectrum comprising of substitutions, deletions and insertions. We developed a human B cell surface display platform and used CODE-HB to evolve neutralizing antibodies targeting avian influenza and escape variants of influenza. Given the modularity and simplicity of CODE-HB, we anticipate that this platform can be used for rapidly evolving biotechnologically relevant biomolecules directly in human cells.

synthetic biology↗