Coupled pre-mRNA and mRNA dynamics unveil operational strategies underlying transcriptional responses to stimuli

Genome-wide simultaneous measurements of pre-mRNA and mRNA expression reveal unexpected time-dependent transcript production and degradation profiles in response to external stimulus, as well as a striking lack of concordance between mRNA abundance and transcript production profiles

Marked Differences in Human Melanoma Antigen-Specific T Cell Responsiveness after Vaccination Using a Functional Microarray

BACKGROUND: In contrast to many animal model studies, immunotherapeutic trials in humans suffering from cancer invariably result in a broad range of outcomes, from long-lasting remissions to no discernable effect. METHODS AND FINDINGS: In order to study the T cell responses in patients undergoing a melanoma-associated peptide vaccine trial, we have developed a high-throughput method using arrays of peptide-major histocompatibility complexes (pMHC) together with antibodies against secreted factors. T cells were specifically immobilized and activated by binding to particular pMHCs. The antibodies, spotted together with the pMHC, specifically capture cytokines secreted by the T cells. This technique allows rapid, simultaneous isolation and multiparametric functional characterization of antigen-specific T cells present in clinical samples. Analysis of CD8+ lymphocytes from ten melanoma patients after peptide vaccination revealed a diverse set of patient- and antigen-specific profiles of cytokine secretion, indicating surprising differences in their responsiveness. Four out of four patients who showed moderate or greater secretion of both interferon-γ (IFNγ) and tumor necrosis factor-α (TNFα) in response to a gp100 antigen remained free of melanoma recurrence, whereas only two of six patients who showed discordant secretion of IFNγ and TNFα did so. CONCLUSION: Such multiparametric analysis of T cell antigen specificity and function provides a valuable tool with which to dissect the molecular underpinnings of immune responsiveness and how this information correlates with clinical outcome

Detection and Characterizationof Cellular Immune Responses Using Peptide–MHC Microarrays

The detection and characterization of antigen-specific T cell populations is critical for understanding the development and physiology of the immune system and its responses in health and disease. We have developed and tested a method that uses arrays of peptide–MHC complexes for the rapid identification, isolation, activation, and characterization of multiple antigen-specific populations of T cells. CD4(+) or CD8(+) lymphocytes can be captured in accordance with their ligand specificity using an array of peptide–MHC complexes printed on a film-coated glass surface. We have characterized the specificity and sensitivity of a peptide–MHC array using labeled lymphocytes from T cell receptor transgenic mice. In addition, we were able to use the array to detect a rare population of antigen-specific T cells following vaccination of a normal mouse. This approach should be useful for epitope discovery, as well as for characterization and analysis of multiple epitope-specific T cell populations during immune responses associated with viral and bacterial infection, cancer, autoimmunity, and vaccination

Functional proteomics screen enables enrichment of distinct cell types from human pancreatic islets.

The current world-wide epidemic of diabetes has prompted attempts to generate new sources of insulin-producing cells for cell replacement therapy. An inherent challenge in many of these strategies is the lack of cell-surface markers permitting isolation and characterization of specific cell types from differentiating stem cell populations. Here we introduce an iterative proteomics procedure allowing tag-free isolation of cell types based on their function. Our method detects and associates specific cell-surface markers with particular cell functionality by coupling cell capture on antibody arrays with immunofluorescent labeling. Using this approach in an iterative manner, we discovered marker combinations capable of enriching for discrete pancreatic cell subtypes from human islets of Langerhans: insulin-producing beta cells (CD9high/CD56+), glucagon-producing alpha cells (CD9-/CD56+) and trypsin-producing acinar cells (CD9-/CD56-). This strategy may assist future beta cell research and the development of diagnostic tools for diabetes. It can also be applied more generally for function-based purification of desired cell types from other limited and heterogeneous biological samples

Darwinian selection of host and bacteria supports emergence of Lamarckian-like adaptation of the system as a whole

Background The relatively fast selection of symbiotic bacteria within hosts and the potential transmission of these bacteria across generations of hosts raise the question of whether interactions between host and bacteria support emergent adaptive capabilities beyond those of germ-free hosts. Results To investigate possibilities for emergent adaptations that may distinguish composite host-microbiome systems from germ-free hosts, we introduce a population genetics model of a host-microbiome system with vertical transmission of bacteria. The host and its bacteria are jointly exposed to a toxic agent, creating a toxic stress that can be alleviated by selection of resistant individuals and by secretion of a detoxification agent (“detox”). We show that toxic exposure in one generation of hosts leads to selection of resistant bacteria, which in turn, increases the toxic tolerance of the host’s offspring. Prolonged exposure to toxin over many host generations promotes anadditional form of emergent adaptation due to selection of hosts based on detox produced by their bacterial community as a whole (as opposed to properties of individual bacteria). Conclusions These findings show that interactions between pure Darwinian selections of host and its bacteria can give rise to emergent adaptive capabilities, including Lamarckian-like adaptation of the host-microbiome system. Reviewers This article was reviewed by Eugene Koonin, Yuri Wolf and Philippe Huneman

Epigenetically Heritable Alteration of Fly Development in Response to Toxic Challenge

Developing organisms have evolved a wide range of mechanisms for coping with recurrent environmental challenges. How they cope with rare or unforeseen challenges is, however, unclear as are the implications to their unchallenged offspring. Here, we investigate these questions by confronting the development of the fly, D. melanogaster, with artificial tissue distributions of toxic stress that are not expected to occur during fly development. We show that under a wide range of toxic scenarios, this challenge can lead to modified development that may coincide with increased tolerance to an otherwise lethal condition. Part of this response was mediated by suppression of Polycomb group genes, which in turn leads to derepression of developmental regulators and their expression in new domains. Importantly, some of the developmental alterations were epigenetically inherited by subsequent generations of unchallenged offspring. These results show that the environment can induce alternative patterns of development that are stable across multiple generations

Identification and validation of markers for initial enrichment of specific cell types within human islets of Langerhans.

<p><b>(a)</b> Representative images of populated antibody spots with different enrichments of insulin- (red), glucagon- (green) and somatostatin-positive cells (blue). On the right are spots mostly populated by non-endocrine cells, and on the left are spots populated by different proportions of alpha, beta and delta cells. Corresponding phase contrast images are shown on the right of each image (10x magnification). <b>(b)</b> Real-time qPCR analysis of several cell-type specific genes in different marker-isolated populations (insulin for beta cells, glucagon for alpha cells, somatostatin for delta cells and trypsin for acinar cells). CD9⁺ refers to top 10% expressing cells (CD9^high). Shown is mean expression relative to unsorted (bulk) cells +/- SE (n = 3; biological replicates correspond to different donors; * p < 0.05, ** p < 0.01).</p