Influence of the Wavelength of Excitation and Fluorescence Emission Detection on the Estimation of Fluorescence-Based Physiological Parameters in Different Classes of Photosynthetic Organisms

Fluorescence-based methodologies are commonly employed to determine a wide spectrum of physiological parameters in intact photosynthetic organisms. These methods rely on the detection of Chlorophyll a fluorescent emission, which exhibits changes in its intensity due to the occurrence of quenching phenomena of either photochemical or non-photochemical nature, as well as in response of the absorption cross-section of the photosystems. At room temperature, it is generally considered that most of the emission stems from Photosystem II, and therefore, most of the physiological parameters rely on the assumption that contribution from Photosystem I is negligible. Moreover, it is often considered that the whole light-harvesting antenna is efficiently coupled to either of the photosystems and does not contribute, independently, to the detected emission. When these caveats are not realised, fluorescence-based indicators might be subjected to biases that tend to underestimate the extent of both photochemical and non-photochemical quenching. The contribution of Photosystem I and partially coupled/antenna components can be assessed through the analysis of the dependency of steady-state emission as a function of both the excitation and the emission wavelengths. On this basis, methods relying on using different combinations of excitation and emission wavelengths will be discussed in order to minimise the bias on the estimation of physiologically relevant parameters

PD-1 is a regulator of virus-specific CD8+ T cell survival in HIV infection

Here, we report on the expression of programmed death (PD)-1 on human virus-specific CD8+ T cells and the effect of manipulating signaling through PD-1 on the survival, proliferation, and cytokine function of these cells. PD-1 expression was found to be low on naive CD8+ T cells and increased on memory CD8+ T cells according to antigen specificity. Memory CD8+ T cells specific for poorly controlled chronic persistent virus (HIV) more frequently expressed PD-1 than memory CD8+ T cells specific for well-controlled persistent virus (cytomegalovirus) or acute (vaccinia) viruses. PD-1 expression was independent of maturational markers on memory CD8+ T cells and was not directly associated with an inability to produce cytokines. Importantly, the level of PD-1 surface expression was the primary determinant of apoptosis sensitivity of virus-specific CD8+ T cells. Manipulation of PD-1 led to changes in the ability of the cells to survive and expand, which, over several days, affected the number of cells expressing cytokines. Therefore, PD-1 is a major regulator of apoptosis that can impact the frequency of antiviral T cells in chronic infections such as HIV, and could be manipulated to improve HIV-specific CD8+ T cell numbers, but possibly not all functions in vivo

Deconvolving the contributions of cell-type heterogeneity on cortical gene expression

Complexity of cell-type composition has created much skepticism surrounding the interpretation of bulk tissue transcriptomic studies. Recent studies have shown that deconvolution algorithms can be applied to computationally estimate cell-type proportions from gene expression data of bulk blood samples, but their performance when applied to brain tissue is unclear. Here, we have generated an immunohistochemistry (IHC) dataset for five major cell-types from brain tissue of 70 individuals, who also have bulk cortical gene expression data. With the IHC data as the benchmark, this resource enables quantitative assessment of deconvolution algorithms for brain tissue. We apply existing deconvolution algorithms to brain tissue by using marker sets derived from human brain single cell and cell-sorted RNA-seq data. We show that these algorithms can indeed produce informative estimates of constituent cell-type proportions. In fact, neuronal subpopulations can also be estimated from bulk brain tissue samples. Further, we show that including the cell-type proportion estimates as confounding factors is important for reducing false associations between Alzheimer\u27s disease phenotypes and gene expression. Lastly, we demonstrate that using more accurate marker sets can substantially improve statistical power in detecting cell-type specific expression quantitative trait loci (eQTLs)

Preferential infection and depletion of Mycobacterium tuberculosis–specific CD4 T cells after HIV-1 infection

HIV-1 preferentially infects M. tuberculosis-specific CD4+ T cells due to their increased production of IL-2

Application of B cell immortalization for the isolation of antibodies and B cell clones from vaccine and infection settings

The isolation and characterization of neutralizing antibodies from infection and vaccine settings informs future vaccine design, and methodologies that streamline the isolation of antibodies and the generation of B cell clones are of great interest. Retroviral transduction to express Bcl-6 and Bcl-xL and transform primary B cells has been shown to promote long-term B cell survival and antibody secretion in vitro, and can be used to isolate antibodies from memory B cells. However, application of this methodology to B cell subsets from different tissues and B cells from chronically infected individuals has not been well characterized. Here, we characterize Bcl-6/Bcl-xL B cell immortalization across multiple tissue types and B cell subsets in healthy and HIV-1 infected individuals, as well as individuals recovering from malaria. In healthy individuals, naïve and memory B cell subsets from PBMCs and tonsil tissue transformed with similar efficiencies, and displayed similar characteristics with respect to their longevity and immunoglobulin secretion. In HIV-1-viremic individuals or in individuals with recent malaria infections, the exhausted CD27-CD21- memory B cells transformed with lower efficiency, but the transformed B cells expanded and secreted IgG with similar efficiency. Importantly, we show that this methodology can be used to isolate broadly neutralizing antibodies from HIV-infected individuals. Overall, we demonstrate that Bcl-6/Bcl-xL B cell immortalization can be used to isolate antibodies and generate B cell clones from different B cell populations, albeit with varying efficiencies

Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines

The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy. © 2013 IEEE

Finding the functional consequences of genetic risk loci on gene expression and DNA methylation by integrating contextual information

The majority of genetic loci that influence complex traits are non-coding. Roughly half of these loci affect gene expression in one or more tissues, despite making up less than 10% of common genetic variants. However, it is increasingly unlikely that genetic effects on gene expression will be sufficient to assign a function to all non-coding risk loci. This thesis splits the problem of assigning new functions to complex trait loci into two steps. First, I aim to increase the number of non-coding loci with a known function without requiring new molecular datasets. In my thesis, I explore context-dependent genetic regulation of molecular traits, where the context that affects this process is either inferred from data or a common phenotypic measure like sex. I then advocate for associating genetic variation with molecular data other than gene expression, primarily on DNA methylation. Second, I outline how to tie these novel molecular functions to genetic risk for complex traits. Importantly, this requires methods and workflows that summarize genetic effects at individual loci across interpretable functional units (genes) and genome-wide genetic risk for complex traits. In my scholarship chapters, I first show that environments inferred from global gene expression can correlate with various phenotypic and environmental variables. These inferred contexts are replicated across samples and can subsequently be used to identify novel context-specific genetic regulation of gene expression. I then show that novel context-specific genetic regulation can be approached in DNA methylation using sex, measured in virtually all genetic and molecular datasets. My later chapters demonstrate how to summarize genetic effects to learn which traits are particularly relevant to these novel regulatory relationships. I start with effects and individual loci and then explore methods to interpret the gene-level influence of genetic effects on DNA methylation. Then I demonstrate how cumulative, genome-wide risk for complex traits can provide new insight into the biological functions underlying complex traits beyond the effects I observe at individual loci. Overall this thesis shows that we require various approaches to discover disease-relevant molecular functions of non-coding genetic loci.Science, Faculty ofGraduat

Sex-dependent placental mQTL provide insight into the prenatal origins of childhood-onset traits and conditions

Placental mQTL from term placental subjects, meta-analyzed across the NICHD and RICHS cohort