Bayesian modeling of air pollution extremes using nested multivariate max‐stable processes

Capturing the potentially strong dependence among the peak concentrations of multiple air pollutants across a spatial region is crucial for assessing the related public health risks. In order to investigate the multivariate spatial dependence properties of air pollution extremes, we introduce a new class of multivariate max‐stable processes. Our proposed model admits a hierarchical tree‐based formulation, in which the data are conditionally independent given some latent nested positive stable random factors. The hierarchical structure facilitates Bayesian inference and offers a convenient and interpretable characterization. We fit this nested multivariate max‐stable model to the maxima of air pollution concentrations and temperatures recorded at a number of sites in the Los Angeles area, showing that the proposed model succeeds in capturing their complex tail dependence structure.     

Visualizing Cell-to-cell Transfer of HIV using Fluorescent Clones of HIV and Live Confocal Microscopy

By fusing the green fluorescent protein to their favorite proteins, biologists now have the ability to study living complex cellular processes using fluorescence video microscopy. To track the movements of the human immunodeficiency virus core protein during cell-to-cell transmission of human immunodeficiency virus, we have GFP-tagged the Gag protein in the context of an infectious molecular clone of HIV, called HIV Gag-iGFP. We study this viral clone using video confocal microscopy. In the following visualized experiment, we transfect a human T cell line with HIV Gag-iGFP, and we use fluorescently labeled uninfected CD4+ T cells to serve as target cells for the virus. Using the different fluorescent labels we can readily follow viral production and transport across intercellular structures called virological synapses. Simple gas permeable imaging chambers allow us to observe synapses with live confocal microscopy from minutes to days. These approaches can be used to track viral proteins as they move in from one cell to the next.Download video file.^{(80M, mov)}     

Differential Imaging of Biological Structures with Doubly-resonant Coherent Anti-stokes Raman Scattering (CARS)

Coherent Raman imaging techniques have seen a dramatic increase in activity over the past decade due to their promise to enable label-free optical imaging with high molecular specificity ¹. The sensitivity of these techniques, however, is many orders of magnitude weaker than fluorescence, requiring milli-molar molecular concentrations ^1,2. Here, we describe a technique that can enable the detection of weak or low concentrations of Raman-active molecules by amplifying their signal with that obtained from strong or abundant Raman scatterers. The interaction of short pulsed lasers in a biological sample generates a variety of coherent Raman scattering signals, each of which carry unique chemical information about the sample. Typically, only one of these signals, e.g. Coherent Anti-stokes Raman scattering (CARS), is used to generate an image while the others are discarded. However, when these other signals, including 3-color CARS and four-wave mixing (FWM), are collected and compared to the CARS signal, otherwise difficult to detect information can be extracted ³. For example, doubly-resonant CARS (DR-CARS) is the result of the constructive interference between two resonant signals ⁴. We demonstrate how tuning of the three lasers required to produce DR-CARS signals to the 2845 cm^-1 CH stretch vibration in lipids and the 2120 cm^-1 CD stretching vibration of a deuterated molecule (e.g. deuterated sugars, fatty acids, etc.) can be utilized to probe both Raman resonances simultaneously. Under these conditions, in addition to CARS signals from each resonance, a combined DR-CARS signal probing both is also generated. We demonstrate how detecting the difference between the DR-CARS signal and the amplifying signal from an abundant molecule''s vibration can be used to enhance the sensitivity for the weaker signal. We further demonstrate that this approach even extends to applications where both signals are generated from different molecules, such that e.g. using the strong Raman signal of a solvent can enhance the weak Raman signal of a dilute solute.     

Monitoring dynamic protein expression in living E. coli. Bacterial cells by laser tweezers Raman spectroscopy.

BACKGROUND: Laser tweezers Raman spectroscopy (LTRS) is a novel, nondestructive, and label-free method that can be used to quantitatively measure changes in cellular activity in single living cells. Here, we demonstrate its use to monitor changes in a population of E. coli cells that occur during overexpression of a protein, the extracellular domain of myelin oligodendrocyte glycoprotein [MOG(1-120)]. METHODS: Raman spectra were acquired from individual E. coli cells suspended in solution and trapped by a single tightly focused laser beam. Overexpression of MOG(1-120) in transformed E. coli Rosetta-Gami (DE3)pLysS cells was induced by addition of isopropyl thiogalactoside (IPTG). Changes in the peak intensities of the Raman spectra from a population of cells were monitored and analyzed over a total duration of 3 h. Data were also collected for concentrated purified MOG(1-120) protein in solution, and the spectra compared with that obtained for the MOG(1-120) expressing cells. RESULTS: Raman spectra of individual, living E. coli cells exhibit signatures due to DNA and protein molecular vibrations. Characteristic Raman markers associated with protein vibrations, such as 1,257, 1,340, 1,453, and 1,660 cm(-1), are shown to increase as a function of time following the addition of IPTG. Comparison of these spectra and the spectra of purified MOG protein indicates that the changes are predominantly due to the induction of MOG protein expression. Protein expression was found to occur mostly within the second hour, with a 470% increase relative to the protein expressed in the first hour. A 230% relative increase between the second and third hour indicates that protein expression begins to level off within the third hour. CONCLUSION: It is demonstrated that LTRS has sufficient sensitivity for real-time, nondestructive, and quantitative monitoring of biological processes, such as protein expression, in single living cells. Such capabilities, which are not currently available in flow cytometry, open up new possibilities for analyzing cellular processes occurring in single microbial and eukaryotic cells.     

Stoichiometry of reconstituted high-density lipoproteins in the hydrated state determined by photon antibunching

Apolipoprotein A-I plays a central role in the solution structure of high-density lipoproteins. Determining the stoichiometry of lipid-bound apo A-I in the hydrated state is therefore fundamental to understanding how high-density lipoproteins form and function. Here, we use the quantum optical phenomenon of photon antibunching to determine the number of apo A-I molecules bound to discoidal lipoproteins and compare this with values obtained by photon-counting histogram analysis. Both the photon antibunching and photon-counting analyses show that reconstituted high-density lipoprotein particles contain two apo A-I molecules, which is in agreement with the commonly accepted double-belt model.     

Plant- and microbe-derived compounds affect the expression of genes encoding antifungal compounds in a pseudomonad with biocontrol activity

We have investigated the impacts of 63 different low-molecular-weight compounds, most of them plant derived, on the in vitro expression of two antifungal biosynthetic genes by the plant-protecting rhizobacterium Pseudomonas fluorescens CHA0. The majority of the compounds tested affected the expression of one or both antifungal genes. This suggests that biocontrol activity in plant-beneficial pseudomonads is modulated by plant-bacterium signaling.