Biology subjects

Amir, A.

Publications and source records attributed to Amir, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Using Bayesian inference to characterize cell-size regulation across organisms

How organisms regulate cell size and whether this varies with growth conditions remains a fundamental question. Inferring how cells regulate their size requires separating biological control from statistical effects. Yet regulatory strategies are commonly classified by estimating the size-control parameter, , from single-cell measurements using linear regression. We show that this conventional estimator is systematically biased by measurement noise, lineage-to-lineage extrinsic variability, and finite lineage length. Consequently, the same underlying regulatory mechanism can be misclassified as sizer-, adder-, or timer-like. We develop a Bayesian framework that jointly infers and the amplitudes of intrinsic, extrinsic, and measurement noise while accounting for lineage heterogeneity and finite sampling. Across simulations spanning experimentally relevant noise levels and lineage lengths, the framework recovers and outperforms conventional regression, particularly for short and heterogeneous lineages. Reanalysis of diverse bacterial and eukaryotic datasets collected under multiple growth conditions indicates that statistical bias accounts for much of the reported variation in across organisms and growth conditions. After accounting for these biases, the datasets are broadly consistent with adder-like regulation. Thus, our results provide a general framework for distinguishing genuine biological differences from noise-induced changes in inferred regulatory strategy and revise how cell-size regulation should be inferred from lineage data.

biophysics↗

bioRxiv2026

From Flocks to Swarms: Rewriting the Rules of Collective Cell Migration

From flocking birds to swarming insects, collective motion enables groups to accomplish tasks beyond the capabilities of individuals. These behaviors emerge from local interactions among group members, but the interaction rules that organize collectives at the cellular scale remain poorly understood, in part because they are difficult to manipulate experimentally. Here we develop a cell-machine interface that enables us to rewrite the rules of collective migration. Cell-cell interaction rules are specified in software and implemented in living cells through real-time computer vision and closed-loop optogenetic control. Using a single engineered cell line, we program cells to self-organize into flocks, to propagate regenerative signal relays that recapitulate the interaction logic of immune-cell swarms, and to collectively navigate guidance cues that individual cells cannot. Our work shows that altering simple rules of cell-cell interaction is sufficient to generate new emergent collective capabilities. This approach provides an experimental framework for discovering the organizational principles of multicellular coordination and designing synthetic collectives with capabilities beyond those of their individual members.

synthetic biology↗

bioRxiv2026

Functional Characterization of Transcriptome-Wide Isoform Switching in Hürthle Cell Carcinoma (HCC)

Hurthle cell carcinoma (HCC) is an aggressive form of thyroid cancer. While mitochondrial DNA mutations and chromosomal losses have been identified in HCC, isoform switching, and its functional consequences remain uncharacterized. This study reanalyzed NCBI GEO dataset GSE228870 (n = 32), using Salmon and IsoformSwitchAnalyzeR() to identify isoform switching. The analysis resulted in 371 switches across 335 genes showing functional consequences including loss of protein domains, shorter open reading frames (ORFs), loss of signal peptides and novel sub-cellular localizations. Most significant isoform switches (q-value < 0.05, |dIF| > 0.1) were observed in LAMA2, LSP1, MAD2L2, FBLN2 and CXCL12, implicating extracellular matrix dysregulation, DNA damage response, immune signaling and cytoskeleton regulation. These genes are expressed in normal thyroid (median TPM 20.69, 11.66, 14.79, 134.1 & 80.76). However, specific isoforms of LAMA2 and MAD2L2 are not expressed in normal thyroid, explaining tumor-specific expression in HCC. Alternative transcription termination site (ATTS) gain was significant, suggesting altered 3 end in HCC transcripts. TCGA SpliceSeq showed LSP1, FBLN2 and CXCL12 undergo alternative promoter (LSP1 exon1 PSI=94.5%, FBLN2 exon2 PSI=99.0%) and alternative termination (CXCL12 exon3.3 PSI=53.9%) in thyroid cancer, suggesting ATTS and alternative transcription start site (ATSS) as shared splicing dysregulation mechanisms. This is the first systematic characterization of isoform-level dysregulation in HCC.

bioinformatics↗

bioRxiv2026

Bacterial RNA polymerase exemplifies a general physical mechanism for accelerating protein-DNA association

Bacterial RNA polymerases (RNAPs) have two flexibly tethered subunit C-terminal domains (-CTDs) that bind DNA. Interaction between -CTDs and some promoter DNA motifs is known to accelerate transcription initiation, but the physical mechanism by which it does so is unclear. We used single-molecule multiwavelength fluorescence microscopy to test how the diffusion-limited binding kinetics of core RNAP to non-promoter DNA differ from those of mutant RNAPs that lack one or both -CTDs. We find that even though -CTDs and their tethers are small compared to the complete RNAP molecule, the presence of two -CTDs accelerates DNA binding by [~]10-fold and [~]55-fold respectively relative to RNAP constructs in which one or both -CTDs are deleted. In contrast, the presence of -CTDs did not have a detectable effect on RNAP-DNA complex lifetimes in the absence of RNA synthesis. We explain how -CTDs achieve the dramatic acceleration of RNAP binding to DNA using a quantitative three-state kinetic model that includes a transient binding intermediate where only the -CTD(s) are bound to DNA, tethering the rest of the RNAP in the vicinity of DNA. The model and assumed parameters are validated using Brownian dynamics simulations of the DNA association reactions for two-, one-, or zero-CTD RNAP constructs. The combination of single-molecule experiments, mathematical theory, and simulations suggests that adding a flexible DNA-binding tether is a general physical mechanism which can accelerate the diffusion-limited binding of a large protein like RNAP to DNA and quantitatively defines the conditions under which this acceleration can occur. Significance StatementLarge enzymes that must associate with DNA to perform their biological functions are expected to bind DNA only slowly because of slow enzyme diffusion. However, some DNA-binding enzymes have one or more additional small DNA-binding domains that can diffuse rapidly but are attached to the enzyme through an unstructured flexible tether. Combining single-molecule experiments, theory, and computation, we present evidence for a general mechanism by which such tethered domains can accelerate enzyme binding to DNA by orders of magnitude, while not significantly changing the duration of the DNA-bound state. We demonstrate this effect for the flexibly-tethered -subunit C-terminal domain of bacterial RNA polymerase. The mechanism may allow the polymerase to rapidly bind DNA while minimizing non-functional sequestration on the genome.

biophysics↗

bioRxiv2026

Disentangling mechanisms of single-cell growth rate fluctuations

Single-cell growth rates fluctuate across time and generations, but identifying the biological origin of this variability is difficult because growth rate is usually inferred from noisy measurements of cell size or mass rather than measured directly. Here, we develop a simple and interpretable framework that separates measurement noise from biological sources of growth rate variability. We show that the autocovariance of inferred instantaneous growth rates carries robust signatures of the measurement process that are largely independent of the underlying biological growth dynamics, allowing the form and magnitude of measurement noise to be identified directly from data before introducing a model for the biological dynamics. We then use the autocovariance of accumulated growth to distinguish continuous within-cycle fluctuations, division-associated perturbations, and lineage-to-lineage variability. Applying this framework to bacterial and mammalian single-cell datasets, we find evidence for continuous growth rate noise in both systems. In E. coli, division-associated perturbations are large at birth compared with continuous fluctuations, but their contribution to growth accumulated over the full cell cycle is reduced by rapid relaxation. In contrast, mammalian cells show no division kicks, but stronger lineage-to-lineage variability. More broadly, our results provide a direct and interpretable route to identifying the biological origin of growth rate variability in noisy single-cell measurements.

cell biology↗

bioRxiv2026

A UNIFORM CODING STRUCTURE IN THE CEREBRAL CORTEX

Prefrontal neurons simultaneously encode multiple task variables. While many studies reported that various groupings of task features could be detected at the population level, the combination of features encoded by individual neurons seemed random. Here, based on unit recordings with Neuropixel probes in behaving rats, we report that far from being random, the representation of information is highly structured. Specifically, the prefrontal network exhibits multiple coding gradients orthogonal to each other in a multidimensional representational space. In this coding structure, neurons have correlated absolute firing rate modulations by different variables, but the polarity of the modulation by one variable is not predictive of that by others. Moreover, this coding structure is manifest in tasks that probe different behavioral processes, ranging from defensive behaviors to sensory discrimination. Last, we find that the same structured representation is apparent in other neocortical regions, including associative and primary sensory areas.

neuroscience↗

bioRxiv2026

Cell Growth and Division Shape mRNA-Protein Correlations

1Correlations between cellular variables, such as gene-expression levels, provide insights into regulatory mechanisms. We focus here on correlations between mRNA and protein levels and re-examine previously derived analytical predictions. We test this prediction on single-cell E. coli data and see substantial disagreement. We hypothesize that this discrepancy arises from the assumption of constant cell volume and develop a theoretical framework for mRNA-protein correlations in growing and dividing cells. Within this framework, we derive an analytical expression for mRNA- protein correlations and show that explicit incorporation of growth and division substantially alters these correlations. The resulting relation is invariant to upstream transcriptional dynamics, and we validate it using stochastic simulations across multiple gene-regulatory architectures. Finally, we show that the derived predictions are consistent with the E. coli data.

biophysics↗

bioRxiv2026

Contributions of error correction and the spindle assembly checkpoint to mitotic timing and fidelity

Chromosome segregation is a tightly-regulated process that normally occurs with high fidelity. Errors in chromosome segregation are associated with aging, cancer, and infertility. Initially erroneously attached chromosomes are corrected over the course of mitosis, with the spindle assembly checkpoint preventing entry into anaphase until this error correction is complete. Despite extensive work on the molecular basis of error correction and the spindle assembly checkpoint, it is still unclear how disruption of these processes contribute to chromosome segregation errors. Here, we develop and experimentally test a coarse-grained model of error correction in the presence of a faulty spindle assembly checkpoint. We use the resulting model to disentangle the impact of various small molecule and genetic perturbations on both error correction and the spindle assembly checkpoint, and to compare chromosomally stable hTERT-RPE-1 cells and chromosomally unstable U2-OS cells. We find that the probability of error-free chromosome segregation is determined by the ratio of the checkpoint failure rate to the error correction rate, and validate a simple heuristic for understanding the source of chromosome segregation errors: perturbations which cause errors by disrupting the spindle assembly checkpoint decrease anaphase times, while those that disrupt error correction increase anaphase times. Taken together, this work provides a quantitative framework for understanding how error correction and the spindle assembly checkpoint contribute to mitotic timing and fidelity.

biophysics↗

bioRxiv2025

Biologically-constrained insect models enable realistic simulations and improve biomechanical predictions of locomotion

Animal locomotion emerges from the complex interplay of morphology, neural control, and biomechanics, involving both active and passive elements. Insect have attracted much interest, and a rich ecosystem of computational models exists for insect locomotion. However, while active control mechanisms have been extensively studied, obtaining accurate and useful models remains challenging due to limited understanding of how detailed anatomical constraints and passive biomechanical properties shape movement. To address this, we developed anatomically accurate 3D models of the adult desert locust and mole cricket, two orthopteran insects that share a basic body plan but exhibit strikingly different morphologies linked to their habitats and specialized locomotor behaviors -- jumping in locusts versus subterranean digging in mole crickets. We fine-tuned these models using precise morphometric measurements for each major body segment. Furthermore, we quantified passive joint dynamics through high-speed videography of anesthetized locust, revealing a two-phase return motion and history-dependent resting angles. By integrating these biologically grounded constraints into physical simulations, we significantly narrowed the parameter space, resulting in more realistic simulations. Our approach provides new tools for predicting biologically relevant, yet experimentally challenging variables, such as joint torques and contact forces, which contribute directly to the understanding of the underlying biological phenomena. Moreover, these improved simulations offer valuable insight for designing energy-efficient soft robotic systems.

animal behavior and cognition↗

bioRxiv2025

Stochasticity in mammalian cell growth rates drives cell-to-cell variability independently of cell size and divisions

Cell growth rates exhibit cell-intrinsic cell-to-cell variability, which influences cell fitness and size home-ostasis from bacteria to cancer. Whether this variability arises from noise in cell growth or cell division processes, or originates from cell-size-dependent growth rates, remains unclear. To separate these potential sources of growth variability, single-cell growth rates need to be examined across different timescales. Here, we study cell-intrinsic size and growth regulation by tracking lymphocytic leukemia cell mass accumulation with high precision and minute-scale temporal resolution along long ancestral lineages. We first show that cell-size-dependent growth regulation and asymmetric division of cell size do not explain cell-to-cell growth variability. We then isolate growth fluctuations from overlapping cell-cycle-dependent growth using a Gaussian process regression analysis. We find that these growth fluctuations drive cell-to-cell growth variability within ancestral lineages despite being independent of cell divisions, cell cycle, and cell size. Overall, our results indicate that cell-intrinsic long-term patterns in cell growth are a byproduct of short-term growth fluctuations.

systems biology↗

bioRxiv2025

Multiple locomotion gaits in the mole cricket

Insects are exceptionally robust walkers. Although different species exhibit distinct anatomical and functional specializations, they are also highly adaptive within these constraints. How such adaptations enable insects to efficiently navigate diverse environments and perform mechanical tasks remains far from fully explored. The mole cricket, which dwells underground, is one of the least studied insects, largely due to its cryptic lifestyle. It excels at digging tunnels and exhibits extreme morphological adaptations, particularly its exceptional fossorial forelegs. Its versatile locomotion, above and below ground, makes the mole cricket an attractive model system for studying the biomechanics of insect movement. Here we provide the first quantitative characterization of mole cricket locomotion. Using a tunnel-like arena, we recorded freely-moving insects and analyzed their various locomotion gaits. We identified and described three main modes of locomotion, including a backward-bound gait that has not previously been reported in any insect. To test specific hypotheses regarding form-function relationships and the generation of thrust, we integrated biomechanical modeling and deep reinforcement learning to simulate the observed gaits. Our work opens several future directions, from exploring context-dependent gait transitions to bio-inspired technological innovations.

animal behavior and cognition↗

bioRxiv2024

Design principles of transcription factors with intrinsically disordered regions

Transcription Factors (TFs) are proteins crucial for regulating gene expression. Effective regulation requires the TFs to rapidly bind to their correct target, enabling the cell to respond efficiently to stimuli such as nutrient availability or the presence of toxins. However, the search process is hindered by slow diffusive movement and the presence of false targets - DNA segments that are similar to the true target. In eukaryotic cells, most TFs contain an Intrinsically Disordered Region (IDR), which is commonly assumed to behave as a long, flexible polymeric tail composed of hundreds of amino acids. Recent experimental findings indicate that the IDR of certain TFs plays a pivotal role in the search process. However, the principles underlying the IDRs role remain unclear. Here, we reveal key design principles of the IDR related to TF binding affinity and search time. Our results demonstrate that the IDR significantly enhances both of these aspects. Furthermore, our model shows good agreement with experimental results, and we propose further experiments to validate the models predictions.

biophysics↗

bioRxiv2024

Six-legged-bound: a newly-described insect gait

Locomotor behavior is a hallmark of animal biology and ecology. Mole crickets constitute a unique group of subterranean insects that present an exceptional model for locomotion-related research. In response to an aversive stimulus from the front, the mole cricket will consistently adopt a unique backwards gait that we have termed backward-bound. This never before reported six-legged gait comprises a cyclic alternation between the middle and hind-leg pairs with left-right in-phase synchronization, while the front legs display noisy and less consistent phase dynamics. This exceptional gait is transient and is usually expressed for up to a dozen cycles. It is employed to distance the animal quickly away from danger. A gait that can be characterized as "forward-bound" is also displayed by the mole cricket, albeit for a much shorter duration (up to two cycles).

animal behavior and cognition↗

bioRxiv2024

Are cell length and volume interchangeable in cell cycle analysis?

Cell length has been used as a proxy for cell size in cell cycle modeling studies. A previous study, however, brought into question the validity of this assumption, noting that correlations between cell lengths can be different from those involving cell volume if cell width fluctuations are taken into account. If cell volume is regulated, data analysis involving cell lengths will lead to an incorrect inference of the cell size control mechanism. We used conditional correlation of length variables conditioned upon radius variables to elucidate the underlying volume control mechanism. Using the conditional correlation on previous mother machine datasets measuring lengths at birth and division, and the cell radius for multiple cells, we find that the cell volume control strategy is consistent with an adder model. Further, using the conditional correlation, we conclude that measurement noise constitutes a significant portion of the radius variability in the experimental datasets. To conclude, cell length and cell volume can often be used interchangeably owing to small cell width fluctuations.

biophysics↗

bioRxiv2024

Determining the rate-limiting processes for cell division in Escherichia coli

A critical cell cycle checkpoint for most bacteria is the onset of constriction when the septal peptidoglycan synthesis starts. According to the current understanding, the arrival of FtsN to midcell triggers this checkpoint in Escherichia coli. Recent structural and in vitro data suggests that recruitment of FtsN to the Z-ring leads to a conformational switch in actin-like FtsA, which links FtsZ protofilaments to the cell membrane and acts as a hub for the late divisome proteins. Here, we investigate this putative pathway using in vivo measurements and stochastic cell cycle modeling. Quantitatively upregulating protein concentrations and determining the resulting division timings shows that FtsN and FtsA numbers are not rate-limiting for the division in E. coli. However, at higher overexpression levels, they affect divisions: FtsN by accelerating and FtsA by inhibiting them. At the same time, we find that the numbers of FtsZ in the cell are rate-limiting for cell divisions in addition to other processes. Altogether, these findings suggest that instead of FtsN, FtsZ protofilaments drive the conformational switch of FtsA and lead to the onset of constriction. Our data is also suggestive that FtsA minirings are not present at any significant numbers in wild-type cells.

cell biology↗

bioRxiv2024

Measuring and modeling the dynamics of mitotic error correction

Error correction is central to many biological systems and is critical for protein function and cell health. During mitosis, error correction is required for the faithful inheritance of genetic material. When functioning properly, the mitotic spindle segregates an equal number of chromosomes to daughter cells with high fidelity. Over the course of spindle assembly, many initially erroneous attachments between kinetochores and microtubules are fixed through the process of error correction. Despite the importance of chromosome segregation errors in cancer and other diseases, there is a lack of methods to characterize the dynamics of error correction and how it can go wrong. Here, we present an experimental method and analysis framework to quantify chromosome segregation error correction in human tissue culture cells with live cell confocal imaging, timed premature anaphase, and automated counting of kinetochores after cell division. We find that errors decrease exponentially over time during spindle assembly. A coarse-grained model, in which errors are corrected in a chromosome autonomous manner at a constant rate, can quantitatively explain both the measured error correction dynamics and the distribution of anaphase onset times. We further validated our model using perturbations that destabilized microtubules and changed the initial configuration of chromosomal attachments. Taken together, this work provides a quantitative framework for understanding the dynamics of mitotic error correction.

cell biology↗

bioRxiv2023

Putting cognitive tasks on trial: A measure of reliability convergence

The surge in interest in individual differences has coincided with the latest replication crisis centered around brain-wide association studies of brain-behavior correlations. Yet the reliability of the measures we use in cognitive neuroscience, a crucial component of this brain-behavior relationship, is often assumed but not directly tested. Here, we evaluate the reliability of different cognitive tasks on a large dataset of over 250 participants, who each completed a multi-day task battery. We show how reliability improves as a function of number of trials, and describe the convergence of the reliability curves for the different tasks, allowing us to score tasks according to their suitability for studies of individual differences. To improve the accessibility of these findings, we designed a simple web-based tool that implements this function to calculate the convergence factor and predict the expected reliability for any given number of trials and participants, even based on limited pilot data.

neuroscience↗

bioRxiv2023

Self-extinguishing relay waves enable homeostaticcontrol of human neutrophil swarming

Neutrophils exhibit self-amplified swarming to sites of injury and infection. How swarming is controlled to ensure the proper level of neutrophil recruitment is unknown. Using an ex vivo model of infection, we find that human neutrophils use active relay to generate multiple pulsatile waves of swarming signals. Unlike classic active relay systems such as action potentials, neutrophil swarming relay waves are self-extinguishing, limiting the spatial range of cell recruitment. We identify an NADPH-oxidase-based negative feedback loop that is needed for this self-extinguishing behavior. Through this circuit, neutrophils adjust the number and size of swarming waves for homeostatic levels of cell recruitment over a wide range of initial cell densities. We link a broken homeostat to neutrophil over-recruitment in the context of human chronic granulomatous disease.

cell biology↗