Biology subjects

Mayo, A.

Publications and source records attributed to Mayo, A..

30 records · Page 2Linked to original sources

bioRxiv2022

Damage dynamics in single E. coli and the role of chance in the timing of cell death

Genetically identical cells in the same stressful condition die at different times. The origin of this stochasticity is unclear; it may arise from different initial conditions that affect the time of demise, or from a stochastic damage accumulation mechanism that erases the initial conditions and instead amplifies noise to generate different lifespans. To address this requires measuring damage dynamics in individual cells over the lifespan, but this has rarely been achieved. Here, we used a microfluidic device to measure membrane damage in 648 carbon-starved E. coli cells at high temporal resolution. We find that initial conditions of damage, size or cell-cycle phase do not explain most of the lifespan variation. Instead, the data points to a stochastic mechanism in which noise is amplified by a rising production of damage that saturates its own removal. Surprisingly, the relative variation in damage drops with age: cells become more similar to each other in terms of relative damage, indicating increasing determinism with age. Thus, chance erases initial conditions and then gives way to increasingly deterministic dynamics that dominate the lifespan distribution.

systems biology↗

bioRxiv2022

Tradeoffs in bacterial physiology determine the efficiency of antibiotic killing

Antibiotics can kill or stop the growth of bacteria, and their effectiveness depends on many factors. It is important to understand the relation between bacterial physiology, the environment and antibiotic action. While many of the mechanistic details of antibiotic action are known, the connection between death rate and bacterial physiology is poorly understood. Death rate in antibiotics has often been shown to rise linearly with growth rate; however, it remains unclear how environmental factors, in concert with whole-cell physiological properties, affect bactericidal activity. To address this, we developed a high-throughput assay to precisely measure antibiotic-mediated bacterial death. We found that death rate is linear in growth rate, but the slope depends on environmental conditions. Specifically, stressors lower the death rate compared to a non-stressed environment with the same growth rate. To understand the role of stress, we developed a mathematical model of bacterial death based on resource allocation that takes into account a newly defined stress-response sector; we identify this sector using RNA-seq. Our model accurately predicts the death rate and minimal inhibitory concentration of antibiotics across a wide range of conditions, including a previously unknown increase in the stress response and protection from death at very low levels of cAMP. The present death-growth model suggests conditions that may improve antibiotic efficacy.

systems biology↗

bioRxiv2020

Human hormone seasonality

Hormones control the major biological functions of stress response, growth, metabolism and reproduction. In animals these hormones show pronounced seasonality, with different set-points for different seasons. In humans, the seasonality of these hormones remains unclear, due to a lack of datasets large enough to discern common patterns and cover all hormones. Here, we analyze an Israeli health record on 46 million person-years, including millions of hormone blood tests. We find clear seasonal patterns: the effector hormones peak in winter-spring, whereas most of their upstream regulating pituitary hormones peak only months later, in summer. This delay of months is unexpected because known delays in the hormone circuits last hours. We explain the precise delays and amplitudes by proposing and testing a mechanism for the circannual clock: the gland masses grow with a timescale of months due to trophic effects of the hormones, generating a feedback circuit with a natural frequency of about a year that can entrain to the seasons. Thus, humans may show coordinated seasonal set-points with a winter-spring peak in the growth, stress, metabolism and reproduction axes.

systems biology↗

bioRxiv2020

A High Throughput Gravimetric Phenotyping Platform for Real Time Physiological Screening of Plant Environment Dynamic Responses

Food security for the growing global population is a major concern. The data provided by genomic tools far exceeds the supply of phenotypic data, creating a knowledge gap. To meet the challenge of improving crops to feed the growing global population, this gap must be bridged. Physiological traits are considered key functional traits in the context of responsiveness or sensitivity to environmental conditions. Many recently introduced high-throughput phenotyping techniques are based on remote sensing or imaging and are capable of directly measuring morphological traits, but measure physiological parameters only indirectly. This paper describes a method for direct physiological phenotyping that has several advantages for the functional phenotyping of plant-environment interactions. It aims to help users overcome the many challenges encountered in the use of load-cell gravimetric systems and pot experiments. The suggested techniques will enable users to distinguish between soil weight, plant weight and soil water content, providing a method for continuous and simultaneous measurement of dynamic soil, plant and atmosphere conditions, alongside key physiological traits. This method allows researchers to closely mimic field stress scenarios while taking into consideration the environments effect on the plants physiology. This method also minimizes pot effects, which are one of the major problems in pre-field phenotyping. It includes a feedback fertigation system that enables a truly randomized experimental design with a field-like plant density. This system detects the soil-water content limiting threshold ({theta}) and allows for the translation of data into knowledge through the use of a real-time analytic tool and an online statistical resource. This method for the rapid and direct measurement of the physiological responses of multiple plants to a dynamic environment has great potential for use in screening for beneficial traits associated with responses to abiotic stress, in the context of pre-field breeding and crop improvement. SUMMARYThis high-throughput, whole-plant water relations gravimetric phenotyping method enables direct and simultaneous real-time measurements and analysis of multiple yield-related physiological traits involved in dynamic plant-environment interactions.

plant biology↗

bioRxiv2020

Cancer-associated fibroblast compositions change with breast cancer progression linking S100A4 and PDPN ratios with clinical outcome

Tumors are supported by cancer-associated fibroblasts (CAFs). CAFs are heterogeneous and carry out distinct cancer-associated functions. Understanding the full repertoire of CAFs and their dynamic changes could improve the precision of cancer treatment. CAFs are usually analyzed at a single time-point using specific markers, and it is therefore unclear whether CAFs display plasticity as tumors evolve. Here, we analyze thousands of CAFs using index and transcriptional single-cell sorting, at several time-points along breast tumor progression in mice, uncovering distinct subpopulations. Strikingly, the transcriptional programs of these subpopulations change over time and in metastases, transitioning from an immune-regulatory program to wound healing and antigen-presentation programs, indicating that CAFs and their functions are dynamic. Two main CAF subpopulations are also found in human breast tumors, where their ratio is associated with disease outcome across subtypes, and is particularly correlated with BRCA mutations in triple-negative breast cancer. These findings indicate that the repertoire of CAFs changes over time in breast cancer progression, with direct clinical implications.

cancer biology↗

bioRxiv2019

Endocrine autoimmune disease as a fragility of immune-surveillance against hypersecreting mutants

Many endocrine organs show prevalent autoimmune diseases (AID) such as type-1-diabetes and Hashimotos-thyroiditis. The fundamental origins of these diseases is unclear. Here we address AID from the viewpoint of feedback control. Endocrine tissues maintain their mass by feedback-loops that balance cell proliferation and removal according to input signals related to the hormone function. Such feedback is unstable to mutant cells that mis-sense the signal, and therefore hyper-proliferate and hyper-secrete the hormone. We hypothesize that in order to prevent these mutants from expanding, each organ has a dedicated autoimmune surveillance of hyper-secreting mutants (ASHM), in which hyper-secreting cells are preferentially eliminated, at the cost of a fragility to AID. ASHM correctly predicts the identity of the self-antigens and the presence of T-cells against these self-antigens in healthy individuals. It offers a predictive theory for which tissues get frequent AID, and which do not and instead show frequent mutant-expansion disease (e.g. hyperparathyroidism).

immunology↗

bioRxiv2019

Evolution toward maximum transport capacity of the Ttg2 ABC system in Pseudomonas aeruginosa

In Pseudomonas aeruginosa, Ttg2D is the soluble periplasmic phospholipid-binding component of an ABC transport system thought to be involved in maintaining the asymmetry of the outer membrane. The crystallographic structure of Ttg2D at 2.5[A] resolution reveals that this protein can bind two diacyl phospholipids. Native and denaturing mass spectrometry experiments confirm that Ttg2D binds two phospholipid molecules, which may have different head groups. Analysis of the available structures of Ttg2D orthologs allowed us to classify this protein family as a novel substrate-binding protein fold and to venture the evolutionary events that differentiated the orthologs binding one or two phospholipids. In addition, gene knockout experiments in P. aeruginosa PAO1 and multidrug-resistant strains show that disruption of this system leads to outer membrane permeabilization. This demonstrates the role of this system in low-level intrinsic resistance against certain antibiotics that use a lipid-mediated pathway to permeate through membranes.

microbiology↗

bioRxiv2019

Principles of Cell Circuits for Tissue Repair and Fibrosis

Tissue-repair is a protective response after injury, but repetitive or prolonged injury can lead to fibrosis, a pathological state of excessive scarring. To pinpoint the dynamic mechanisms underlying fibrosis, it is important to understand the principles of the cell circuits that carry out tissue-repair. In this study, we establish a cell-circuit framework for the myofibroblast-macrophage circuit in wound-healing, including the accumulation of scar-forming extracellular matrix. We find that fibrosis results from multistability between three outcomes, which we term hot fibrosis characterized by many macrophages, cold fibrosis lacking macrophages, and normal wound-healing. The cell-circuit framework clarifies several unexplained phenomena including the paradoxical effect of macrophage depletion, the limited time-window in which removing inflammation leads to healing, the effects of cellular senescence, and why scar maturation takes months. We define key parameters that control the transition from healing to fibrosis, which may serve as potential targets for therapeutic reduction of fibrosis.

systems biology↗

bioRxiv2018

Central dogma rates and the trade-off between precision and economy

Steady-state protein abundance is set by four rates: transcription, translation, mRNA decay and protein decay. A given protein abundance can be obtained from infinitely many combinations of these rates. This raises the question of whether the natural rates for each gene result from historical accidents, or are there rules that give certain combinations a selective advantage? We address this question using high-throughput measurements in rapidly growing cells from diverse organisms to find that about half of the rate combinations do not exist: genes that combine high transcription with low translation are strongly depleted. This depletion is due to a trade-off between precision and economy: high transcription decreases stochastic fluctuations but increases transcription costs. Our theory quantitatively explains which rate combinations are missing, and predicts the curvature of the fitness function for each gene. It may guide the design of gene circuits with desired expression levels and noise.

systems biology↗

bioRxiv2018

Evolutionary tradeoffs and the structure of allelic polymorphisms

Populations of organisms show prevalent genetic differences called polymorphisms. Understanding the effects of polymorphisms is of central importance in biology and medicine. Here, we ask which polymorphisms occur at high frequency when organisms evolve under tradeoffs between multiple tasks. Multiple tasks present a problem, because it is not possible to be optimal at all tasks simultaneously and hence compromises are necessary. Recent work indicates that tradeoffs lead to a simple geometry of phenotypes in the space of traits: phenotypes fall on the Pareto front, which is shaped as a polytope: a line, triangle, tetrahedron etc. The vertices of these polytopes are the optimal phenotypes for a single task. Up to now, work on this Pareto approach has not considered its genetic underpinnings. Here, we address this by asking how the polymorphism structure of a population is affected by evolution under tradeoffs. We simulate a multi-task selection scenario, in which the population evolves to the Pareto front: the line segment between two archetypes or the triangle between three archetypes. We find that polymorphisms that become prevalent in the population have pleiotropic phenotypic effects that align with the Pareto front. Similarly, epistatic effects between prevalent polymorphisms are parallel to the front. Alignment with the front occurs also for asexual mating. Alignment is reduced when drift or linkage is strong, and is replaced by a more complex structure in which many perpendicular allele effects cancel out. Aligned polymorphism structure allows mating to produce offspring that stand a good chance of being optimal multi-taskers in at least one of the locales available to the species.

systems biology↗

bioRxiv2016

Neuronal components of evaluating the human 1 origin of abstract shapes

Communication through visual symbols is a key aspect of human culture. However, to what extent can people distinguish between human-origin and artificial symbols, and the neuronal mechanisms underlying this process are not clear. Using fMRI we contrasted brain activity during presentation of human-created abstract shapes and random-algorithm created shapes, both sharing similar low level features.\n\nWe found that participants correctly identified most shapes as human or random. The lateral occipital complex (LOC) was the main brain region showing preference to human-made shapes, independently of task. Furthermore, LOC activity was parametrically correlated to beauty and familiarity scores of the shapes (rated following the scan). Finally, a model classifier based only on LOC activity showed human level accuracy at discriminating between human-made and randomly-made shapes.\n\nOur results highlight the sensitivity of the human brain to social and cultural cues, and point to high-order object areas as central nodes underlying this capacity.

neuroscience↗

bioRxiv2016

Dynamic proteomics of HSV1 infection reveals molecular events that govern non-stochastic infection outcomes

Viral infection is usually studied at the level of cell populations, averaging over hundreds of thousands of individual cells. Moreover, measurements are typically done by analyzing a few time points along the infection process. While informative, such measurements are limited in addressing how cell variability affects infection outcome. Here we employ dynamic proteomics to study virus-host interactions, using the human pathogen Herpes Simplex virus 1 as a model. We tracked >50,000 individual cells as they respond to HSV1 infection, allowing us to model infection kinetics and link infection outcome (productive or not) with the cell state at the time of initial infection. We find that single cells differ in their preexisting susceptibility to HSV1, and that this is partially mediated by their cell-cycle position. We also identify specific changes in protein levels and localization in infected cells, attesting to the power of the dynamic proteomics approach for studying virus-host interactions.

systems biology↗