While it has been established that a number of microenvironment components can affect the likelihood of metastasis, the link between microenvironment and tumor cell phenotypes is poorly understood. ...Here we have examined microenvironment control over two different tumor cell motility phenotypes required for metastasis. By high-resolution multiphoton microscopy of mammary carcinoma in mice, we detected two phenotypes of motile tumor cells, different in locomotion speed. Only slower tumor cells exhibited protrusions with molecular, morphological, and functional characteristics associated with invadopodia. Each region in the primary tumor exhibited either fast- or slow-locomotion. To understand how the tumor microenvironment controls invadopodium formation and tumor cell locomotion, we systematically analyzed components of the microenvironment previously associated with cell invasion and migration. No single microenvironmental property was able to predict the locations of tumor cell phenotypes in the tumor if used in isolation or combined linearly. To solve this, we utilized the support vector machine (SVM) algorithm to classify phenotypes in a nonlinear fashion. This approach identified conditions that promoted either motility phenotype. We then demonstrated that varying one of the conditions may change tumor cell behavior only in a context-dependent manner. In addition, to establish the link between phenotypes and cell fates, we photoconverted and monitored the fate of tumor cells in different microenvironments, finding that only tumor cells in the invadopodium-rich microenvironments degraded extracellular matrix (ECM) and disseminated. The number of invadopodia positively correlated with degradation, while the inhibiting metalloproteases eliminated degradation and lung metastasis, consistent with a direct link among invadopodia, ECM degradation, and metastasis. We have detected and characterized two phenotypes of motile tumor cells in vivo, which occurred in spatially distinct microenvironments of primary tumors. We show how machine-learning analysis can classify heterogeneous microenvironments in vivo to enable prediction of motility phenotypes and tumor cell fate. The ability to predict the locations of tumor cell behavior leading to metastasis in breast cancer models may lead towards understanding the heterogeneity of response to treatment.
Cell cycle quiescence is a critical feature contributing to haematopoietic stem cell (HSC) maintenance. Although various candidate stromal cells have been identified as potential HSC niches, the ...spatial localization of quiescent HSCs in the bone marrow remains unclear. Here, using a novel approach that combines whole-mount confocal immunofluorescence imaging techniques and computational modelling to analyse significant three-dimensional associations in the mouse bone marrow among vascular structures, stromal cells and HSCs, we show that quiescent HSCs associate specifically with small arterioles that are preferentially found in endosteal bone marrow. These arterioles are ensheathed exclusively by rare NG2 (also known as CSPG4)(+) pericytes, distinct from sinusoid-associated leptin receptor (LEPR)(+) cells. Pharmacological or genetic activation of the HSC cell cycle alters the distribution of HSCs from NG2(+) periarteriolar niches to LEPR(+) perisinusoidal niches. Conditional depletion of NG2(+) cells induces HSC cycling and reduces functional long-term repopulating HSCs in the bone marrow. These results thus indicate that arteriolar niches are indispensable for maintaining HSC quiescence.
Epigenetic regulatory mechanisms allow multicellular organisms to develop distinct specialized cell identities despite having the same total genome. Cell-fate choices are based on gene expression ...programs and environmental cues that cells experience during embryonic development, and are usually maintained throughout the life of the organism despite new environmental cues. The evolutionarily conserved Polycomb group (PcG) proteins form Polycomb Repressive Complexes that help orchestrate these developmental choices. Post-development, these complexes actively maintain the resulting cell fate, even in the face of environmental perturbations. Given the crucial role of these polycomb mechanisms in providing phenotypic fidelity (i.e. maintenance of cell fate), we hypothesize that their dysregulation after development will lead to decreased phenotypic fidelity allowing dysregulated cells to sustainably switch their phenotype in response to environmental changes. We call this abnormal phenotypic switching phenotypic pliancy. We introduce a general computational evolutionary model that allows us to test our systems-level phenotypic pliancy hypothesis in-silico and in a context-independent manner. We find that 1) phenotypic fidelity is an emergent systems-level property of PcG-like mechanism evolution, and 2) phenotypic pliancy is an emergent systems-level property resulting from this mechanism's dysregulation. Since there is evidence that metastatic cells behave in a phenotypically pliant manner, we hypothesize that progression to metastasis is driven by the emergence of phenotypic pliancy in cancer cells as a result of PcG mechanism dysregulation. We corroborate our hypothesis using single-cell RNA-sequencing data from metastatic cancers. We find that metastatic cancer cells are phenotypically pliant in the same manner as predicted by our model.
The coronavirus disease 2019 (COVID-19) pandemic currently in process differs from other infectious disease calamities that have previously plagued humanity in the vast amount of information that is ...produced each day, which includes daily estimates of the disease incidence and mortality data. Apart from providing actionable information to public health authorities on the trend of the pandemic, the daily incidence reflects the process of disease in a susceptible population and thus reflects the pathogenesis of COVID-19, the public health response, and diagnosis and reporting. Both new daily cases and daily mortality data in the United States exhibit periodic oscillatory patterns. By analyzing New York City (NYC) and Los Angeles (LA) testing data, we demonstrate that this oscillation in the number of cases can be strongly explained by the daily variation in testing. This seems to rule out alternative hypotheses, such as increased infections on certain days of the week, as driving this oscillation. Similarly, we show that the apparent oscillation in mortality in the U.S. data are mostly an artifact of reporting, which disappears in data sets that record death by episode date, such as the NYC and LA data sets. Periodic oscillations in COVID-19 incidence and mortality data reflect testing and reporting practices and contingencies. Thus, these contingencies should be considered first prior to suggesting biological mechanisms.
The incidence and mortality data for the COVID-19 data in the United States show periodic oscillations, giving the curve a distinctive serrated pattern. In this study, we show that these periodic highs and lows in incidence and mortality data are due to daily differences in testing for the virus and death reporting, respectively. These findings are important because they provide an explanation based on public health practices and shortcomings rather than biological explanations, such as infection dynamics. In other words, when oscillations occur in epidemiological data, a search for causes should begin with how the public health system produces and reports the information before considering other causes, such as infection cycles and higher incidences of events on certain days. Our results suggest that when oscillations occur in epidemiological data, this may be a signal that there are shortcomings in the public health system generating that information.
Molecular noise is a natural phenomenon that is inherent to all biological systems
. How stochastic processes give rise to the robust outcomes that support tissue homeostasis remains unclear. Here we ...use single-molecule RNA fluorescent in situ hybridization (smFISH) on mouse stem cells derived from haematopoietic tissue to measure the transcription dynamics of three key genes that encode transcription factors: PU.1 (also known as Spi1), Gata1 and Gata2. We find that infrequent, stochastic bursts of transcription result in the co-expression of these antagonistic transcription factors in the majority of haematopoietic stem and progenitor cells. Moreover, by pairing smFISH with time-lapse microscopy and the analysis of pedigrees, we find that although individual stem-cell clones produce descendants that are in transcriptionally related states-akin to a transcriptional priming phenomenon-the underlying transition dynamics between states are best captured by stochastic and reversible models. As such, a stochastic process can produce cellular behaviours that may be incorrectly inferred to have arisen from deterministic dynamics. We propose a model whereby the intrinsic stochasticity of gene expression facilitates, rather than impedes, the concomitant maintenance of transcriptional plasticity and stem cell robustness.
Endothermy and homeothermy are mammalian characteristics whose evolutionary origins are poorly understood. Given that fungal species rapidly lose their capacity for growth above ambient temperatures, ...we have proposed that mammalian endothermy enhances fitness by creating exclusionary thermal zones that protect against fungal disease. According to this view, the relative paucity of invasive fungal diseases in immunologically intact mammals relative to other infectious diseases would reflect an inability of most fungal species to establish themselves in a mammalian host. In this study, that hypothesis was tested by modeling the fitness increase with temperature versus its metabolic costs. We analyzed the tradeoff involved between the costs of the excess metabolic rates required to maintain a body temperature and the benefit gained by creating a thermal exclusion zone that protects against environmental microbes such as fungi. The result yields an optimum at 36.7°C, which closely approximates mammalian body temperatures. This calculation is consistent with and supportive of the notion that an intrinsic thermally based resistance against fungal diseases could have contributed to the success of mammals in the Tertiary relative to that of other vertebrates.
Protocell multilevel selection models have been proposed to study the evolutionary dynamics of vesicles encapsulating a set of replicating, competing and mutating sequences. The frequency of the ...different sequence types determines protocell survival through a fitness function. One of the defining features of these models is the genetic load generated when the protocell divides and its sequences are assorted between the offspring vesicles. However, these stochastic assortment effects disappear when the redundancy of each sequence type is sufficiently high. The fitness dependence of the vesicle with its sequence content is usually defined without considering a realistic account on how the lower level dynamics would specify the protocell fitness. Here, we present a protocell model with a fitness function determined by the output flux of a simple metabolic network with the aim of understanding how the evolution of both kinetic and topological features of metabolism would have been constrained by the particularities of the protocell evolutionary dynamics. In our model, the sequences inside the vesicle are both the carriers of information and Michaelis-Menten catalysts exhibiting saturation. We found that the saturation of the catalysts controlling the metabolic fluxes, achievable by modifying the kinetic or stoichiometric parameters, provides a mechanism to ameliorate the assortment load by increasing the redundancy of the catalytic sequences required to achieve the maximum flux. Regarding the network architecture, we conclude that combinations of parallel network motifs and bimolecular catalysts are a robust way to increase the complexity of the metabolism enclosed by the protocell.
An evolutionary capacitor buffers genotypic variation under normal conditions, thereby promoting the accumulation of hidden polymorphism. But it occasionally fails, thereby revealing this variation ...phenotypically. The principal example of an evolutionary capacitor is Hsp90, a molecular chaperone that targets an important set of signal transduction proteins. Experiments in Drosophila and Arabidopsis have demonstrated three key properties of Hsp90: (1) it suppresses phenotypic variation under normal conditions and releases this variation when functionally compromised; (2) its function is overwhelmed by environmental stress; and (3) it exerts pleiotropic effects on key developmental processes. But whether these properties necessarily make Hsp90 a significant and unique facilitator of adaptation is unclear. Here we use numerical simulations of complex gene networks, as well as genome-scale expression data from yeast single-gene deletion strains, to present a mechanism that extends the scope of evolutionary capacitance beyond the action of Hsp90 alone. We illustrate that most, and perhaps all, genes reveal phenotypic variation when functionally compromised, and that the availability of loss-of-function mutations accelerates adaptation to a new optimum phenotype. However, this effect does not require the mutations to be conditional on the environment. Thus, there might exist a large class of evolutionary capacitors whose effects on phenotypic variation complement the systemic, environment-induced effects of Hsp90.
The United States (US) Expanded Access Program (EAP) to coronavirus disease 2019 (COVID-19) convalescent plasma was initiated in response to the rapid spread of severe acute respiratory syndrome ...coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. While randomized clinical trials were in various stages of development and enrollment, there was an urgent need for widespread access to potential therapeutic agents. The objective of this study is to report on the demographic, geographical, and chronological characteristics of patients in the EAP, and key safety metrics following transfusion of COVID-19 convalescent plasma.
Mayo Clinic served as the central institutional review board for all participating facilities, and any US physician could participate as a local physician-principal investigator. Eligible patients were hospitalized, were aged 18 years or older, and had-or were at risk of progression to-severe or life-threatening COVID-19; eligible patients were enrolled through the EAP central website. Blood collection facilities rapidly implemented programs to collect convalescent plasma for hospitalized patients with COVID-19. Demographic and clinical characteristics of all enrolled patients in the EAP were summarized. Temporal patterns in access to COVID-19 convalescent plasma were investigated by comparing daily and weekly changes in EAP enrollment in response to changes in infection rate at the state level. Geographical analyses on access to convalescent plasma included assessing EAP enrollment in all national hospital referral regions, as well as assessing enrollment in metropolitan areas and less populated areas that did not have access to COVID-19 clinical trials. From April 3 to August 23, 2020, 105,717 hospitalized patients with severe or life-threatening COVID-19 were enrolled in the EAP. The majority of patients were 60 years of age or older (57.8%), were male (58.4%), and had overweight or obesity (83.8%). There was substantial inclusion of minorities and underserved populations: 46.4% of patients were of a race other than white, and 37.2% of patients were of Hispanic ethnicity. Chronologically and geographically, increases in the number of both enrollments and transfusions in the EAP closely followed confirmed infections across all 50 states. Nearly all national hospital referral regions enrolled and transfused patients in the EAP, including both in metropolitan and in less populated areas. The incidence of serious adverse events was objectively low (<1%), and the overall crude 30-day mortality rate was 25.2% (95% CI, 25.0% to 25.5%). This registry study was limited by the observational and pragmatic study design that did not include a control or comparator group; thus, the data should not be used to infer definitive treatment effects.
These results suggest that the EAP provided widespread access to COVID-19 convalescent plasma in all 50 states, including for underserved racial and ethnic minority populations. The study design of the EAP may serve as a model for future efforts when broad access to a treatment is needed in response to an emerging infectious disease.
ClinicalTrials.gov NCT#: NCT04338360.
Generalists and specialists are types of strategies individuals can employ that can evolve in fluctuating environments depending on the extremity and periodicity of the fluctuation. To evaluate ...whether the evolution of specialists or generalists occurs under environmental fluctuation regimes with different levels of periodicity, 24 populations of
Escherichia coli
underwent laboratory evolution with temperatures alternating between 15 and 43°C in three fluctuation regimes: two periodic regimes dependent on culture's cell density and one random (non-periodic) regime with no such dependency, serving as a control. To investigate contingencies on the genetic background, we seeded our experiment with two different strains. After the experiment, growth rate measurements at the two temperatures showed that the evolution of specialists was favored in the random regime, while generalists were favored in the periodic regimes. Whole genome sequencing demonstrated that several gene mutations were selected in parallel in the evolving populations with some dependency on the starting genetic background. Given the genes mutated, we hypothesized that the driving force behind the observed adaptations is the restoration of the internal physiology of the starting strains' unstressed states at 37°C, which may be a means of improving fitness in the new environments. Phenotypic array measurements supported our hypothesis by demonstrating a tendency of the phenotypic response of the evolved strains to move closer to the starting strains' response at the optimum of 37°C, especially for strains classified as generalists.
PDF
