The use of mathematical and computational tools in investigating Natural Killer (NK) cell biology and in general the immune system has increased steadily in the last few decades. However, unlike the ...physical sciences, there is a persistent ambivalence, which however is increasingly diminishing, in the biology community toward appreciating the utility of quantitative tools in addressing questions of biological importance. We survey some of the recent developments in the application of quantitative approaches for investigating different problems in NK cell biology and evaluate opportunities and challenges of using quantitative methods in providing biological insights in NK cell biology.
Single Cell Neurometabolomics Qi, Meng; Philip, Marina C; Yang, Ning ...
ACS chemical neuroscience,
01/2018, Volume:
9, Issue:
1
Journal Article
Peer reviewed
Open access
Metabolomics, the characterization of metabolites and their changes within biological systems, has seen great technological and methodological progress over the past decade. Most metabolomic ...experiments involve the characterization of the small-molecule content of fluids or tissue homogenates. While these microliter and larger volume metabolomic measurements can characterize hundreds to thousands of compounds, the coverage of molecular content decreases as sample sizes are reduced to the nanoliter and even to the picoliter volume range. Recent progress has enabled the ability to characterize the major molecules found within specific individual cells. Especially within the brain, a myriad of cell types are colocalized, and oftentimes only a subset of these cells undergo changes in both healthy and pathological states. Here we highlight recent progress in mass spectrometry-based approaches used for single cell metabolomics, emphasizing their application to neuroscience research. Single cell studies can be directed to measuring differences between members of populations of similar cells (e.g., oligodendrocytes), as well as characterizing differences between cell types (e.g., neurons and astrocytes), and are especially useful for measuring changes occurring during different behavior states, exposure to diets and drugs, neuronal activity, and disease. When combined with other omics approaches such as transcriptomics, and with morphological and physiological measurements, single cell metabolomics aids fundamental neurochemical studies, has great potential in pharmaceutical development, and should improve the diagnosis and treatment of brain diseases.
Many tools for studying the pharmacokinetics of biologics lack single-cell resolution to quantify the heterogeneous tissue distribution and subsequent therapeutic degradation in vivo. This protocol ...describes a dual-labeling technique using two near-infrared dyes with widely differing residualization rates to efficiently quantify in vivo therapeutic protein distribution and degradation rates at the single cell level (number of proteins/cell) via ex vivo flow cytometry and histology. Examples are shown for four biologics with varying rates of receptor internalization and degradation and a secondary dye pair for use in systems with lower receptor expression. Organ biodistribution, tissue-level confocal microscopy, and cellular-level flow cytometry were used to image the multi-scale distribution of these agents in tumor xenograft mouse models. The single-cell measurements reveal highly heterogeneous delivery, and degradation results show the delay between peak tumor uptake and maximum protein degradation. This approach has broad applicability in tracking the tissue and cellular distribution of protein therapeutics for drug development and dose determination.
Measurements of distances in cells by pulsed ESR spectroscopy afford tremendous opportunities to study proteins in native environments that are irreproducible in vitro. However, the in-cell ...environment is harsh towards the typical nitroxide radicals used in double electron-electron resonance (DEER) experiments. A systematic examination is performed on the loss of the DEER signal, including contributions from nitroxide decay and nitroxide side-chain cleavage. In addition, the possibility of extending the lifetime of the nitroxide radical by use of an oxidizing agent is investigated. Using this oxidizing agent, DEER distance measurements are performed on doubly nitroxide-labeled GB1, the immunoglobulin-binding domain of protein G, at varying incubation times in the cellular environment. It is found that, by comparison of the loss of DEER signal to the loss of the CW spectrum, cleavage of the nitroxide side chain contributes to the loss of DEER signal, which is significantly greater in cells than in cell extracts. Finally, local spin concentrations are monitored at varying incubation times to show the time required for molecular diffusion of a small globular protein within the cellular milieu.
•Obtain Pmpp of MJ solar cells under temperature and spectral changes are essential.•This allows understanding and predicting the behaviour of MJ solar cells.•The aim of this paper is to define a ...simple way to obtain Pmpp.•A model based on two equivalent solar cells is introduced.•The model predicts Pmpp of a LM triple junction solar cell at one sun condition.
While single junction solar cells are mainly influenced by changes in irradiance and temperature, multi junction concentrator solar cells show complex behaviour as their performance is also strongly influenced by changes in spectrum. Despite this, when studying the system, it is possible to reduce the problem to a set of parameters that could easily be measured and fitted. A simple model to obtain the maximum power point of multi junction solar cells under temperature and spectral changes is proposed. This model is based on a single diode model and is described by a simple set of equations that are easy to fit within a computational program. The model could be useful to understand the behaviour of multi junction solar cells and also CPV technology under real conditions. The main purpose of this paper is to define a simple way to estimate the maximum power point of a multi junction solar cell under spectral and temperature changes at one sun conditions.
Integration of imaging data across different molecular target types can provide in‐depth insight into cell physiology and pathology, but remains challenging owing to poor compatibility between ...target‐type‐specific labeling methods. We show that cross‐platform imaging analysis can be readily achieved through DNA encoding of molecular targets, which translates the molecular identity of various target types into a uniform in situ array of ssDNA tags for subsequent labeling with complementary imaging probes. The concept was demonstrated through multiplexed imaging of mRNAs and their corresponding proteins with multicolor quantum dots. The results reveal heterogeneity of cell transfection with siRNA and outline disparity in RNA interference (RNAi) kinetics at the level of both the mRNA and the encoded protein.
Now you see it: DNA encoding chemistry combined with multiplexed imaging enables simultaneous in situ interrogation of a panel of selected DNA, RNA, and/or protein markers (red, blue, and green probes, respectively) in single cells by bringing different target types onto the same detection platform. In a proof‐of‐concept study with multicolor quantum dot probes, DNA encoding was used to explore the spatial and temporal aspects of cell transfection and RNAi.
Siberian pine (Pinus sibirica Du Tour) is a widespread and long-lived species in the northern hemisphere, which makes it a good potential proxy for climatic data. However, the tree-ring growth of ...this species weakly correlates with climatic conditions, which prevents its use in dendroclimatic reconstruction. It was proposed to use the measurements of tracheid characteristics as model predictors to reconstruct the smoothed temperature of the key periods in tree growth. In this study, algorithms for preprocessing tracheids and temperature data, as well as for model cross-validation, were developed to produce reliable high-resolution (weekly-based) temperature reconstructions. Due to the developed algorithms, the key time periods of Siberian pine growth were identified during the growing season—early June (most active cell development) and mid-July (setting new buds for the next growing season). For these time periods, reliable long-term temperature reconstructions (R2 > 0.6, p < 10−8) were obtained over 1653–2018. The temperature reconstructions significantly correlated (p < 10−8) with independent reanalysis data for the 19th century. The developed approach, based on preprocessing tracheid and temperature data, shows new potential for Siberian pine in high-resolution climate reconstructions and can be applied to other tree species that weakly respond to climate forcing.
Intrathymic development of committed progenitor (pro)-T cells from multipotent hematopoietic precursors offers an opportunity to dissect the molecular circuitry establishing cell identity in response ...to environmental signals. This transition encompasses programmed shutoff of stem/progenitor genes, upregulation of T cell specification genes, proliferation, and ultimately commitment. To explain these features in light of reported cis-acting chromatin effects and experimental kinetic data, we develop a three-level dynamic model of commitment based upon regulation of the commitment-linked gene Bcl11b. The levels are (1) a core gene regulatory network (GRN) architecture from transcription factor (TF) perturbation data, (2) a stochastically controlled chromatin-state gate, and (3) a single-cell proliferation model validated by experimental clonal growth and commitment kinetic assays. Using RNA fluorescence in situ hybridization (FISH) measurements of genes encoding key TFs and measured bulk population dynamics, this single-cell model predicts state-switching kinetics validated by measured clonal proliferation and commitment times. The resulting multi-scale model provides a mechanistic framework for dissecting commitment dynamics.
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•A multi-level dynamical model is developed for the commitment of T cell precursors•It links gene networks, single-cell RNA analysis, chromatin changes, and cell division•It provides quantitative understanding of commitment kinetic requirements•The model predictions are verified against new clonal and real-time imaging data
Olariu et al. use computational modeling and live-cell developmental imaging to explain the kinetics of early T cell lineage commitment. An integrated computational multi-scale model incorporating gene network architecture, single-cell RNA levels, chromatin state shifts, and proliferation is developed, explored, and validated.
Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell ...handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network.
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