Nuclear pore complex-mediated modulation of TCR signaling is required for naïve CD4+ T cell homeostasis.

Nuclear pore complexes (NPCs) are channels connecting the nucleus with the cytoplasm. We report that loss of the tissue-specific NPC component Nup210 causes a severe deficit of naïve CD4+ T cells. Nup210-deficient CD4+ T lymphocytes develop normally but fail to survive in the periphery. The decreased survival results from both an impaired ability to transmit tonic T cell receptor (TCR) signals and increased levels of Fas, which sensitize Nup210-/- naïve CD4+ T cells to Fas-mediated cell death. Mechanistically, Nup210 regulates these processes by modulating the expression of Cav2 (encoding Caveolin-2) and Jun at the nuclear periphery. Whereas the TCR-dependent and CD4+ T cell-specific upregulation of Cav2 is critical for proximal TCR signaling, cJun expression is required for STAT3-dependent repression of Fas. Our results uncover an unexpected role for Nup210 as a cell-intrinsic regulator of TCR signaling and T cell homeostasis and expose NPCs as key players in the adaptive immune system

Computational analysis of microbial flow cytometry data

Flow cytometry is an important technology for the study of microbial communities. It grants the ability to rapidly generate phenotypic single-cell data that are both quantitative, multivariate and of high temporal resolution. The complexity and amount of data necessitate an objective and streamlined data processing workflow that extends beyond commercial instrument software. No full overview of the necessary steps regarding the computational analysis of microbial flow cytometry data currently exists. In this review, we provide an overview of the full data analysis pipeline, ranging from measurement to data interpretation, tailored toward studies in microbial ecology. At every step, we highlight computational methods that are potentially useful, for which we provide a short nontechnical description. We place this overview in the context of a number of open challenges to the field and offer further motivation for the use of standardized flow cytometry in microbial ecology research

Physiological and transcriptomic evidence for a close coupling between chloroplast ontogeny and cell cycle progression in the pennate diatom Seminavis robusta

Despite the growing interest in diatom genomics, detailed time series of gene expression in relation to key cellular processes are still lacking. Here, we investigated the relationships between the cell cycle and chloroplast development in the pennate diatom Seminavis robusta. This diatom possesses two chloroplasts with a well-orchestrated developmental cycle, common to many pennate diatoms. By assessing the effects of induced cell cycle arrest with microscopy and flow cytometry, we found that division and reorganization of the chloroplasts are initiated only after S-phase progression. Next, we quantified the expression of the S. robusta FtsZ homolog to address the division status of chloroplasts during synchronized growth and monitored microscopically their dynamics in relation to nuclear division and silicon deposition. We show that chloroplasts divide and relocate during the S/G2 phase, after which a girdle band is deposited to accommodate cell growth. Synchronized cultures of two genotypes were subsequently used for a cDNA-amplified fragment length polymorphism-based genome-wide transcript profiling, in which 917 reproducibly modulated transcripts were identified. We observed that genes involved in pigment biosynthesis and coding for light-harvesting proteins were up-regulated during G2/M phase and cell separation. Light and cell cycle progression were both found to affect fucoxanthin-chlorophyll a/c-binding protein expression and accumulation of fucoxanthin cell content. Because chloroplasts elongate at the stage of cytokinesis, cell cycle-modulated photosynthetic gene expression and synthesis of pigments in concert with cell division might balance chloroplast growth, which confirms that chloroplast biogenesis in S. robusta is tightly regulated

QFMatch: multidimensional flow and mass cytometry samples alignment

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples

A pipeline for targeted metagenomics of environmental bacteria.

BackgroundMetagenomics and single cell genomics provide a window into the genetic repertoire of yet uncultivated microorganisms, but both methods are usually taxonomically untargeted. The combination of fluorescence in situ hybridization (FISH) and fluorescence activated cell sorting (FACS) has the potential to enrich taxonomically well-defined clades for genomic analyses.MethodsCells hybridized with a taxon-specific FISH probe are enriched based on their fluorescence signal via flow cytometric cell sorting. A recently developed FISH procedure, the hybridization chain reaction (HCR)-FISH, provides the high signal intensities required for flow cytometric sorting while maintaining the integrity of the cellular DNA for subsequent genome sequencing. Sorted cells are subjected to shotgun sequencing, resulting in targeted metagenomes of low diversity.ResultsPure cultures of different taxonomic groups were used to (1) adapt and optimize the HCR-FISH protocol and (2) assess the effects of various cell fixation methods on both the signal intensity for cell sorting and the quality of subsequent genome amplification and sequencing. Best results were obtained for ethanol-fixed cells in terms of both HCR-FISH signal intensity and genome assembly quality. Our newly developed pipeline was successfully applied to a marine plankton sample from the North Sea yielding good quality metagenome assembled genomes from a yet uncultivated flavobacterial clade.ConclusionsWith the developed pipeline, targeted metagenomes at various taxonomic levels can be efficiently retrieved from environmental samples. The resulting metagenome assembled genomes allow for the description of yet uncharacterized microbial clades. Video abstract

Data reduction for spectral clustering to analyze high throughput flow cytometry data

Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular has proven to be a powerful tool amenable for many applications. However, it cannot be directly applied to large datasets due to time and memory limitations. To address this issue, we have modified spectral clustering by adding an information preserving sampling procedure and applying a post-processing stage. We call this entire algorithm SamSPECTRAL.Results: We tested our algorithm on flow cytometry data as an example of large, multidimensional data containing potentially hundreds of thousands of data points (i.e., events in flow cytometry, typically corresponding to cells). Compared to two state of the art model-based flow cytometry clustering methods, SamSPECTRAL demonstrates significant advantages in proper identification of populations with non-elliptical shapes, low density populations close to dense ones, minor subpopulations of a major population and rare populations.Conclusions: This work is the first successful attempt to apply spectral methodology on flow cytometry data. An implementation of our algorithm as an R package is freely available through BioConductor. © 2010 Zare et al; licensee BioMed Central Ltd

Unconventional Repertoire Profile Is Imprinted during Acute Chikungunya Infection for Natural Killer Cells Polarization toward Cytotoxicity

Chikungunya virus (CHIKV) is a worldwide emerging pathogen. In humans it causes a syndrome characterized by high fever, polyarthritis, and in some cases lethal encephalitis. Growing evidence indicates that the innate immune response plays a role in controlling CHIKV infection. We show here that CHIKV induces major but transient modifications in NK-cell phenotype and function soon after the onset of acute infection. We report a transient clonal expansion of NK cells that coexpress CD94/NKG2C and inhibitory receptors for HLA-C1 alleles and are correlated with the viral load. Functional tests reveal cytolytic capacity driven by NK cells in the absence of exogenous signals and severely impaired IFN-γ production. Collectively these data provide insight into the role of this unique subset of NK cells in controlling CHIKV infection by subset-specific expansion in response to acute infection, followed by a contraction phase after viral clearance