Elucidation of Spatial Positioning of Ribosomes around Chromosome in Escherichia coli Cytoplasm via a Data-Informed Polymer-Based Model.

The spatial arrangement of ribosomes and chromosome in Escherichia coli's cytoplasm challenges conventional wisdom. Contrary to the notion of ribosomes acting as inert crowders to the chromosome in the cytoplasm, here we propose a nuanced view by integrating a wide array of experimental data sets into a polymer-based computer model. A set of data-informed computer simulations determines that a delicate balance of attractive and repulsive interactions between ribosomes and the chromosome is required in order to reproduce experimentally obtained linear densities and brings forth the view that ribosomes are not mere inert crowders in the cytoplasm. The model finds that the ribosomes represent themselves as a poor solvent for the chromosome with a 50 nm mesh size, consistent with previous experimental analysis. Our multidimensional analysis of ribosome distribution, both free (30S and 50S) and bound (70S polysome), uncovers a relatively less pronounced segregation pattern than previously thought. Notably, we identify a ribosome-rich central region within the innermost core of the nucleoid. Moreover, our exploration of the chromosome mesh size and the conformation of bound ribosomes suggests that these ribosomes maintain elongated shapes, enabling them to navigate through the chromosome mesh and access the central core. This dynamic localization challenges the static segregation model and underscores the pivotal role of ribosome-chromosome interactions in cellular media.

Development of a Data-Driven Integrative Model of a Bacterial Chromosome.

The chromosome of archetypal bacteria E. coli is known for a complex topology with a 4.6 × 106 base pairs (bp) long sequence of nucleotides packed within a micrometer-sized cellular confinement. The inherent organization underlying this chromosome eludes general consensus due to the lack of a high-resolution picture of its conformation. Here we present our development of an integrative model of E. coli at a 500 bp resolution (https://github.com/JMLab-tifrh/ecoli_finer), which optimally combines a set of multiresolution genome-wide experimentally measured data within a framework of polymer based architecture. In particular the model is informed with an intragenome contact probability map at 5000 bp resolution derived via the Hi-C experiment and RNA-sequencing data at 500 bp resolution. Via dynamical simulations, this data-driven polymer based model generates an appropriate conformational ensemble commensurate with chromosome architectures that E. coli adopts. As a key hallmark of the E. coli chromosome the model spontaneously self-organizes into a set of nonoverlapping macrodomains and suitably locates plectonemic loops near the cell membrane. As novel extensions, it predicts a contact probability map simulated at a higher resolution than precedent experiments and can demonstrate segregation of chromosomes in a partially replicating cell. Finally, the modular nature of the model helps us devise control simulations to quantify the individual role of key features in hierarchical organization of the bacterial chromosome.

Interplay of cell motility and self-secreted extracellular polymeric substance induced depletion effects on spatial patterning in a growing microbial colony.

Reproducing bacteria self-organize to develop patterned biofilms in various conditions. Various factors contribute to the shaping of a multicellular bacterial organization. Here we investigate how motility force and self-secreted extracellular polymeric substances (EPS) influence bacterial cell aggregation, leading to phase-separated colonies using a particle-based/individual-based model. Our findings highlight the critical role of the interplay between motility force and depletion effects in regulating phase separation within a growing colony under far-from-equilibrium conditions. We observe that increased motility force hinders depletion-induced cell aggregation and phase segregation, necessitating a higher depletion effect for highly motile bacteria to undergo phase separation within a growing biofilm. We present a phase diagram illustrating the systematic variation of motility force and repulsive mechanical force, shedding light on the combined contributions of these two factors: self-propulsive motion and aggregation due to the depletion effect, resulting in the presence of small to large bacterial aggregates. Furthermore, our study reveals the dynamic nature of clustering, marked by changes in cluster size over time. Additionally, our findings suggest that differential dispersion among the components can lead to the localization of EPS at the periphery of a growing colony. Our study enhances the understanding of the collective dynamics of motile bacterial cells within a growing colony, particularly in the presence of a self-secreted polymer-driven depletion effect.

Dual enzyme-powered chemotactic cross ß amyloid based functional nanomotors.

Nanomotor chassis constructed from biological precursors and powered by biocatalytic transformations can offer important applications in the future, specifically in emergent biomedical techniques. Herein, cross ß amyloid peptide-based nanomotors (amylobots) were prepared from short amyloid peptides. Owing to their remarkable binding capabilities, these soft constructs are able to host dedicated enzymes to catalyze orthogonal substrates for motility and navigation. Urease helps in powering the self-diffusiophoretic motion, while cytochrome C helps in providing navigation control. Supported by the simulation model, the design principle demonstrates the utilization of two distinct transport behaviours for two different types of enzymes, firstly enhanced diffusivity of urease with increasing fuel (urea) concentration and secondly, chemotactic motility of cytochrome C towards its substrate (pyrogallol). Dual catalytic engines allow the amylobots to be utilized for enhanced catalysis in organic solvent and can thus complement the technological applications of enzymes.

A mechanistic understanding of microcolony morphogenesis: coexistence of mobile and sessile aggregates.

Most bacteria in the natural environment self-organize into collective phases such as cell clusters, swarms, patterned colonies, or biofilms. Several intrinsic and extrinsic factors, such as growth, motion, and physicochemical interactions, govern the occurrence of different phases and their coexistence. Hence, predicting the conditions under which a collective phase emerges due to individual-level interactions is crucial. Here we develop a particle-based biophysical model of bacterial cells and self-secreted extracellular polymeric substances (EPS) to decipher the interplay of growth, motility-mediated dispersal, and mechanical interactions during microcolony morphogenesis. We show that the microcolony dynamics and architecture significantly vary depending upon the heterogeneous EPS production. In particular, microcolony shows the coexistence of both motile and sessile aggregates rendering a transition towards biofilm formation. We identified that the interplay of differential dispersion and the mechanical interactions among the components of the colony determines the fate of the colony morphology. Our results provide a significant understanding of the mechano-self-regulation during biofilm morphogenesis and open up possibilities of designing experiments to test the predictions.

Interpretation of organizational role of proteins on E. coli nucleoid via Hi-C integrated model.

Several proteins in Escherichia coli work together to maintain the complex organization of its chromosome. However, the individual roles of these so-called nucleoid-associated proteins (NAPs) in chromosome architectures are not well characterized. Here, we quantitatively dissect the organizational roles of Heat Unstable (HU), a ubiquitous protein in E. coli and MatP, an NAP specifically binding to the Ter macrodomain of the chromosome. Toward this end, we employ a polymer physics-based computer model of wild-type chromosome and their HU- and MatP-devoid counterparts by incorporating their respective experimentally derived Hi-C contact matrix, cell dimensions, and replication status of the chromosome commensurate with corresponding growth conditions. Specifically, our model for the HU-devoid chromosome corroborates well with the microscopy observation of compaction of chromosome at short genomic range but diminished long-range interactions, justifying precedent hypothesis of segregation defect upon HU removal. Control simulations point out that the change in cell dimension and chromosome content in the process of HU removal holds the key to the observed differences in chromosome architecture between wild-type and HU-devoid cells. On the other hand, simulation of MatP-devoid chromosome led to locally enhanced contacts between Ter and its flanking macrodomains, consistent with previous recombination assay experiments and MatP's role in insulation of the Ter macrodomain from the rest of the chromosome. However, the simulation indicated no change in matS sites' localization. Rather, a set of designed control simulations showed that insulation of Ter is not caused by bridging of distant matS sites, also lending credence to a recent mobility experiment on various loci of the E. coli chromosome. Together, the investigations highlight the ability of an integrative model of the bacterial genome in elucidating the role of NAPs and in reconciling multiple experimental observations.

Hi-C embedded polymer model of Escherichia coli reveals the origin of heterogeneous subdiffusion in chromosomal loci.

Underneath its apparently simple architecture, the circular chromosome of Escherichia coli is known for displaying complex dynamics in its cytoplasm, with past investigations hinting at inherently diverse mobilities of chromosomal loci across the genome. To decipher its origin, we simulate the dynamics of genome-wide spectrum of E. coli chromosomal loci, via integrating its experimentally derived Hi-C interaction matrix within a polymer-based model. Our analysis demonstrates that, while the dynamics of the chromosome is subdiffusive in a viscoelastic media, the diffusion constants are strongly dependent of chromosomal loci coordinates and diffusive exponents (α) are widely heterogenous with α ≈ 0.36-0.60. The loci-dependent heterogeneous dynamics and mean first-passage times of interloci encounter were found to be modulated via genetically distant interloci communications and is robust even in the presence of active, ATP-dependent noises. Control investigations reveal that the absence of Hi-C-derived interactions in the model would have abolished the traits of heterogeneous loci diffusion, underscoring the key role of loci-specific genetically distant interaction in modulating the underlying heterogeneity of the loci diffusion.

Mechanistic underpinning of cell aspect ratio-dependent emergent collective motions in swarming bacteria.

Self-propelled bacteria can exhibit a large variety of non-equilibrium self-organized phenomena. Swarming is one such fascinating dynamical scenario where a number of motile individuals group into dynamical clusters and move in synchronized flows and vortices. While precedent investigations into rod-like particles confirm that an increased aspect-ratio promotes alignment and order, recent experimental studies in bacteria Bacillus subtilis show a non-monotonic dependence of the cell-aspect ratio on their swarming motion. Here, by computer simulations of an agent-based model of self-propelled, mechanically interacting, rod-shaped bacteria under overdamped conditions, we explore the collective dynamics of a bacterial swarm subjected to a variety of cell-aspect ratios. When modeled with an identical self-propulsion speed across a diverse range of cell aspect ratios, simulations demonstrate that both shorter and longer bacteria exhibit slow dynamics whereas the fastest speed is obtained at an intermediate aspect ratio. Our investigation highlights that the origin of this observed non-monotonic trend of bacterial speed and vorticity with the cell-aspect ratio is rooted in the cell-size dependence of motility force. The swarming features remain robust for a wide range of surface density of the cells, whereas asymmetry in friction attributes a distinct effect. Our analysis identifies that at an intermediate aspect ratio, an optimum cell size and motility force promote alignment, which reinforces the mechanical interactions among neighboring cells leading to the overall fastest motion. Mechanistic underpinning of the collective motions reveals that it is a joint venture of the short-range repulsive and the size-dependent motility forces, which determines the characteristics of swarming.