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Mehta, P.

Publications and source records attributed to Mehta, P..

51 records · Page 3Linked to original sources

The effect of resource dynamics on species packing in diverse ecosystems

The competitive exclusion principle asserts that coexisting species must occupy distinct ecological niches (i.e. the number of surviving species can not exceed the number of resources). An open question is to understand if and how different resource dynamics affect this bound. Here, we analyze a generalized consumer resource model with externally supplied resources and show that - in contrast to self-renewing resources - species can occupy only half of all available environmental niches. This motivates us to construct a new schema for classifying ecosystems based on species packing properties.

biophysics↗

Clinical severity in Fanconi anemia correlates with residual function of FANCB missense variants

Fanconi anemia (FA) is the most common genetic cause of bone marrow failure, and is caused by inherited pathogenic variants in any of 22 genes. Of these, only FANCB is X-linked. We describe a cohort of 19 children with FANCB variants, from 16 families of the International Fanconi Anemia Registry (IFAR). Those with FANCB deletion or truncation demonstrate earlier than average onset of bone marrow failure, and more severe congenital abnormalities compared to a large series of FA individuals in the published reports. This reflects the indispensable role of FANCB protein in the enzymatic activation of FANCD2 monoubiquitination, an essential step in the repair of DNA interstrand crosslinks. For FANCB missense variants, more variable severity is associated with the extent of residual FANCD2 monoubiquitination activity. We used transcript analysis, genetic complementation, and biochemical reconstitution of FANCD2 monoubiquitination to determine the pathogenicity of each variant. Aberrant splicing and transcript destabilization was associated with two missence variants. Individuals carrying missense variants with drastically reduced FANCD2 monoubiquitination in biochemical and/or cell-based assays showed earlier onset of hematologic disease and shorter survival. Conversely, variants with near-normal FANCD2 monoubiquitination were associated with more favorable outcome. Our study reveals a genotype-phenotype correlation within the FA-B complementation group of FA, where severity is linked to the extent of residual FANCD2 monoubiquitination.\n\nKEY POINTSO_LIX-linked FANCB pathogenic variants predominantly cause acute, early onset bone marrow failure and severe congenital abnormalities\nC_LIO_LIBiochemical and cell-based assays with patient variants reveal functional properties of FANCB that associate with clinical severity\nC_LI

molecular biology↗

Riluzole does not ameliorate disease caused by cytoplasmic TDP-43 in a mouse model of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease commonly treated with riluzole, a small molecule that may act via modulation of glutamatergic neurotransmission. However, riluzole only modestly extends lifespan for people living with ALS and its precise mechanisms of action remain unclear. Most ALS cases are characterised by accumulation of cytoplasmic TAR DNA binding protein of 43 kDa (TDP-43), and understanding the effects of riluzole in models that closely recapitulate TDP-43 pathology may provide insights for development of improved therapeutics. We therefore investigated the effects of riluzole in transgenic mice that inducibly express nuclear localisation sequence (NLS)-deficient human TDP-43 in neurons (NEFH-tTA/tetO-hTDP-43{Delta}NLS, rNLS, mice). Riluzole treatment from the first day of hTDP-43{Delta}NLS expression did not alter disease onset, weight loss or performance on multiple motor behavioural tasks. Riluzole treatment also did not alter TDP-43 protein levels, solubility or phosphorylation. Although we identified a significant decrease in GluA2 and GluA3 proteins in the cortex of rNLS mice, riluzole did not ameliorate this disease-associated molecular phenotype. Likewise, riluzole did not alter the disease-associated atrophy of hindlimb muscle in rNLS mice. Finally, riluzole treatment beginning after disease onset in rNLS mice similarly had no effect on progression of late-stage disease or animal survival. Together, we demonstrate specific glutamatergic receptor alterations and muscle fibre-type changes reminiscent of ALS in rNLS mice, but riluzole had no effect on these or any other disease phenotypes. Future targeting of pathways directly related to accumulation of TDP-43 pathology may be needed to develop better treatments for ALS. Significance StatementAccumulation of cytoplasmic TDP-43 protein is the hallmark pathology of ALS. Riluzole is the most widely used drug for ALS treatment, but provides only a short extension of lifespan. We demonstrate here in the rNLS mouse model, which mimics TDP-43 pathology, that riluzole does not ameliorate progressive alterations in motor strength and coordination, muscle atrophy, glutamate receptor levels, or TDP-43 protein levels and solubility, and does not prolong animal survival. Riluzole similarly did not affect decreased levels of glutamate receptor subunits GluA2/GluA3 in rNLS mice. The inability of riluzole to rescue pathological or phenotypic changes in this TDP-43 model provides further impetus for the discovery of improved therapies targeting the key drivers of ALS pathogenesis.

neuroscience↗

Single-cell analysis of intestinal immune cells during helminth infection

Single cell isolation from helminth infected intestines has been notoriously difficult, due to the strong anti-parasite type 2 immune responses that drive mucus production, tissue remodeling and immune cell infiltration. Through the systematic optimization of a standard intestinal digestion protocol, we were able to isolate millions of immune cells from heavily infected tissues. Using this protocol, we validated many hallmarks of anti-parasite immunity and analyzed immune cells from the lamina propria and granulomas during helminth development, as well as acute and chronic worm infection.

immunology↗

A minimal model for microbial biodiversity can reproduce experimentally observed ecological patterns

Surveys of microbial biodiversity such as the Earth Microbiome Project (EMP) and the Human Microbiome Project (HMP) have revealed robust ecological patterns across different environments. A major goal in ecology is to leverage these patterns to identify the ecological processes shaping microbial ecosystems. One promising approach is to use minimal models that can relate mechanistic assumptions at the microbe scale to community-level patterns. Here, we demonstrate the utility of this approach by showing that the Microbial Consumer Resource Model (MiCRM) - a minimal model for microbial communities with resource competition, metabolic crossfeeding and stochastic colonization - can qualitatively reproduce patterns found in survey data including compositional gradients, dissimilarity/overlap correlations, richness/harshness correlations, and nestedness of community composition. By using the MiCRM to generate synthetic data with different environmental and taxonomical structure, we show that large scale patterns in the EMP can be reproduced by considering the energetic cost of surviving in harsh environments and HMP patterns may reflect the importance of environmental filtering in shaping competition. We also show that recently discovered dissimilarity-overlap correlations in the HMP likely arise from communities that share similar environments rather than reflecting universal dynamics. We identify ecologically meaningful changes in parameters that alter or destroy each one of these patterns, suggesting new mechanistic hypotheses for further investigation. These findings highlight the promise of minimal models for microbial ecology.

microbiology↗

The Community Simulator: A Python package for microbial ecology

Natural microbial communities contain hundreds to thousands of interacting species. For this reason, computational simulations are playing an increasingly important role in microbial ecology. In this manuscript, we present a new open-source, freely available Python package called Community Simulator for simulating microbial population dynamics in a reproducible, transparent and scalable way. The Community Simulator includes five major elements: tools for preparing the initial states and environmental conditions for a set of samples, automatic generation of dynamical equations based on a dictionary of modeling assumptions, random parameter sampling with tunable levels of metabolic and taxonomic structure, parallel integration of the dynamical equations, and support for metacommunity dynamics with migration between samples. To significantly speed up simulations using Community Simulator, our Python package implements a new Expectation-Maximization (EM) algorithm for finding equilibrium states of community dynamics that exploits a recently discovered duality between ecological dynamics and convex optimization. We present data showing that this EM algorithm improves performance by between one and two orders compared to direct numerical integration of the corresponding ordinary differential equations. We conclude by listing several recent applications of the Community Simulator to problems in microbial ecology, and discussing possible extensions of the package for directly analyzing microbiome compositional data.

ecology↗

Diverse communities behave like typical random ecosystems

With a brief letter to Nature in 1972, Robert May triggered a worldwide research program in theoretical ecology and complex systems that continues to this day[1]. Building on powerful mathematical results about large random matrices, he argued that systems with sufficiently large numbers of interacting components are generically unstable. In the ecological context, Mays thesis directly contradicted the longstanding ecological intuition that diversity promotes stability[2-4]. In economics and finance, Mays work helped to consolidate growing concerns about the fragility of an increasingly interconnected global marketplace[5-7]. In this Letter, we draw on recent theoretical progress in random matrix theory and statistical physics to fundamentally extend and reinterpret Mays theorem. We confirm that a wide range of ecological models become unstable at the point predicted by May, even when the models do not strictly follow his assumptions. Surprisingly, increasing the interaction strength or diversity beyond the May threshold results in a reorganization of the ecosystem - through extinction of a fixed fraction of species - into a new stable state whose properties are well described by purely random interactions. This self-organized state remains stable for arbitrarily large ecosystem and suggests a new interpretation of Mays original conclusions: when interacting complex systems with many components become sufficiently large, they will generically undergo a transition to a \"typical\" self-organized, stable state.

ecology↗

Quantifying the dynamics of hematopoiesis by in vivo IdU pulse-chase, mass cytometry and mathematical modeling

We present a new method to directly quantify the dynamics of differentiation of multiple cellular subsets in unperturbed mice. We combine a pulse-chase protocol of IdU injections with subsequent analysis by mass cytometry (CyTOF), and mathematical modeling of the IdU dynamics. Measurements by CyTOF allow for a wide range of cells to be analyzed at once, due to the availability of a large staining panel without the complication of fluorescence spill-over. These are also compatible with direct detection of integrated iodine signal, with minimal impact on immunophenotyping based on surface markers. Mathematical modeling beyond a binary classification of surface marker abundance allows for a continuum of cellular states as the cells transition from one state to another. Thus, we present a complete and robust method for directly quantifying differentiation at the systemic level, allowing for system-wide comparisons between different mouse strains and/or experimental conditions.

immunology↗

The Minimum Environmental Perturbation Principle: A New Perspective on Niche Theory

Contemporary niche theory is a powerful conceptual framework for understanding how organisms interact with each other and with their shared environment. Here we show that a large segment of niche theory is equivalent to a Minimum Environmental Perturbation Principle (MEPP): ecosystems self-organize into a state that minimizes the impact of organisms on their environment. Different choices of environmental dynamics naturally give rise to distinct dissimilarity measures for quantifying environmental impact. The MEPP allows for the analysis of ecosystems with large numbers of species and environmental factors and provides a new avenue for analyzing ecological invasions. The MEPP also rigorously connects ecological bistability with the existence of multiple minima in a statistical-physics inspired landscapes. We show that the presence of environmental feedbacks where organisms can produce new resources in addition to depleting them violates the global MEPP. However, even in the presence of such feedbacks, a weaker, local version of the MEPP still applies in a limited region of resource space.

ecology↗

The strength of protein-protein interactions controls the information capacity and dynamical response of signaling networks

Eukaryotic cells transmit information by signaling through complex networks of interacting proteins. Here we develop a theoretical and computational framework that relates the biophysics of protein-protein interactions (PPIs) within a signaling network to its information processing properties. To do so, we generalize statistical physics-inspired models for protein binding to account for interactions that depend on post-translational state (e.g. phosphorylation). By combining these models with information-theoretic methods, we find that PPIs are a key determinant of information transmission within a signaling network, with weak interactions giving rise to \"noise\" that diminishes information transmission. While noise can be mitigated by increasing interaction strength, the accompanying increase in transmission comes at the expense of a slower dynamical response. This suggests that the biophysics of signaling protein interactions give rise to a fundamental \"speed-information\" trade-off. Surprisingly, we find that cross-talk between pathways in complex signaling networks do not significantly alter information capacity-an observation that may partially explain the promiscuity and ubiquity of weak PPIs in heavily interconnected networks. We conclude by showing how our framework can be used to design synthetic biochemical networks that maximize information transmission, a procedure we dub \"InfoMax\" design.

systems biology↗

Available energy fluxes drive a phase transition in the diversity, stability, and functional structure of microbial communities

A fundamental goal of microbial ecology is to understand what determines the diversity, stability, and structure of microbial ecosystems. The microbial context poses special conceptual challenges because of the strong mutual influences between the microbes and their chemical environment through the consumption and production of metabolites. By analyzing a generalized consumer resource model that explicitly includes cross-feeding, stochastic colonization, and thermodynamics, we show that complex microbial communities generically exhibit a transition as a function of available energy fluxes from a "resource-limited" regime where community structure and stability is shaped by energetic and metabolic considerations to a diverse regime where the dominant force shaping microbial communities is the overlap between species consumption preferences. These two regimes have distinct species abundance patterns, different functional profiles, and respond differently to environmental perturbations. Our model reproduces large-scale ecological patterns observed across multiple experimental settings such as nestedness and differential beta diversity patterns along energy gradients. We discuss the experimental implications of our results and possible connections with disorder-induced phase transitions in statistical physics.

biophysics↗

Multilabel multiclass classification of OCT images augmented with age, gender and visual acuity data

Optical Coherence Tomography (OCT) imaging of the retina is in widespread clinical use to diagnose a wide range of retinal pathologies and several previous studies have used deep learning to create systems that can accurately classify retinal OCT as indicative of one of these pathologies. However, patients often exhibit multiple pathologies concurrently. Here, we designed a novel neural network algorithm that performs multiclass and multilabel classification of retinal images from OCT images in four common retinal pathologies: epiretinal membrane, diabetic macular edema, dry age-related macular degeneration and neovascular age-related macular degeneration. Furthermore, clinicians often also use additional information about the patient for diagnosis. Second contribution of this study is improvement of multiclass, multilabel classification augmented with information about the patient: age, visual acuity and gender. We compared two training strategies: a network pre-trained with ImageNet was used for transfer learning, or the network was trained from randomly initialized weights. Transfer learning does not perform better in this case, because many of the low-level filters are tuned to colors, and the OCT images are monochromatic. Finally, we provide a transparent and interpretable diagnosis by highlighting the regions recognized by the neural network.

physiology↗

Antimicrobial Efficacy and Safety of a Novel Gas Plasma-Activated Catheter Lock Solution

Antimicrobial lock solutions are important for prevention of microbial colonization and infection of long-term central venous catheters. We investigated the efficacy and safety of a novel antibiotic-free lock solution formed from gas plasma-activated disinfectant (PAD). Using a luminal biofilm model, viable cells of methicillin-resistant Staphylococcus aureus, Staphylococcus epidermidis, Pseudomonas aeruginosa, and Candida albicans in mature biofilms were reduced by 6 - 8 orders of magnitude with a PAD lock for 60 minutes. Subsequent 24-hour incubation of PAD-treated samples resulted in no detectable regrowth of viable bacteria or fungi. As a comparison, the use of a minocycline/EDTA/ethanol lock solution for 60 minutes led to regrowth of bacteria and fungi, up to 107 - 109 CFU/ml, in 24 hours. The PAD lock solution had minimal impact on human umbilical vein endothelial cell viability, whereas the minocycline/EDTA/ethanol solution elicited cell death in nearly half of human endothelial cells. Additionally, PAD treatment caused little topological change to catheter materials. In conclusion, PAD represents a novel antibiotic-free, non-cytotoxic lock solution that elicits rapid and broad-spectrum eradication of biofilm-laden microbes and which shows promise for the prevention and treatment of intravascular catheter infections.

microbiology↗

Emergent Simplicity in Microbial Community Assembly

Microbes assemble into complex, dynamic, and species-rich communities that play critical roles in human health and in the environment. The complexity of natural environments and the large number of niches present in most habitats are often invoked to explain the maintenance of microbial diversity in the presence of competitive exclusion. Here we show that soil and plant-associated microbiota, cultivated ex situ in minimal synthetic environments with a single supplied source of carbon, universally re-assemble into large and dynamically stable communities with strikingly predictable coarse-grained taxonomic and functional compositions. We find that generic, non-specific metabolic cross-feeding leads to the assembly of dense facilitation networks that enable the coexistence of multiple competitors for the supplied carbon source. The inclusion of universal and non-specific cross-feeding in ecological consumer-resource models is sufficient to explain our observations, and predicts a simple determinism in community structure, a property reflected in our experiments.

ecology↗

Environmental engineering is an emergent feature of diverse ecosystems and drives community structure

A central question in ecology is to understand the ecological processes that shape community structure. Niche-based theories have emphasized the important role played by competition for maintaining species diversity. Many of these insights have been derived using MacArthurs consumer resource model (MCRM) or its generalizations. Most theoretical work on the MCRM has focused on small ecosystems with a few species and resources. However theoretical insights derived from small ecosystems many not scale up large ecosystems with many resources and species because large systems with many interacting components often display new emergent behaviors that cannot be understood or deduced from analyzing smaller systems. To address this shortcoming, we develop a sophisticated statistical physics inspired cavity method to analyze MCRM when both the number of species and the number of resources is large. We find that in this limit, species generically and consistently perturb their environments and significantly modify available ecological niches. We show how our cavity approach naturally generalizes niche theory to large ecosystems by accounting for the effect of this emergent environmental engineering on species invasion and ecological stability. Our work suggests that environmental engineering is a generic feature of large, natural ecosystems and must be taken into account when analyzing and interpreting community structure. It also highlights the important role that statistical-physics inspired approaches can play in furthering our understanding of ecology.

ecology↗