The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, ...liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative
de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low-abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.
Previous literature reviews or meta-analysis based studies on game-assisted learning have provided important results, but few studies have considered the importance of learning theory, and coverage ...of papers after 2007 is scant. This study presents a systematic review of the literature using a meta-analysis approach to provide a more comprehensive analysis and synthesis of relevant studies based on four orientations of learning theories and principles: behaviorism, cognitivism, humanism, and constructivism. Major findings of this study include that the majority of published studies were not based on learning theory and the development of learning theory orientations has prompted more studies to focus on constructivism and humanism than on behaviorism and cognitivism. In addition, most studies adopted a descriptive approach, followed by experimental methods and surveys, and most presented positive outcomes. These findings not only advance understanding of game-assisted learning from the important perspective of learning theory, but also provide useful insights for researchers and educators in issues related to game-assisted learning.
► The majority of studies failed to use a foundation of learning theory. ► Studies focused on constructivism and humanism than on behaviorism and cognitivism. ► Studies adopt a descriptive approach, followed by experimental research and surveys. ► Positive outcomes predominate studies based on learning theory.
Cancers arise from successive rounds of mutation and selection, generating clonal populations that vary in size, mutational content and drug responsiveness. Ascertaining the clonal composition of a ...tumor is therefore important both for prognosis and therapy. Mutation counts and frequencies resulting from next-generation sequencing (NGS) potentially reflect a tumor's clonal composition; however, deconvolving NGS data to infer a tumor's clonal structure presents a major challenge. We propose a generative model for NGS data derived from multiple subsections of a single tumor, and we describe an expectation-maximization procedure for estimating the clonal genotypes and relative frequencies using this model. We demonstrate, via simulation, the validity of the approach, and then use our algorithm to assess the clonal composition of a primary breast cancer and associated metastatic lymph node. After dividing the tumor into subsections, we perform exome sequencing for each subsection to assess mutational content, followed by deep sequencing to precisely count normal and variant alleles within each subsection. By quantifying the frequencies of 17 somatic variants, we demonstrate that our algorithm predicts clonal relationships that are both phylogenetically and spatially plausible. Applying this method to larger numbers of tumors should cast light on the clonal evolution of cancers in space and time.
Kaposi's Sarcoma associated Herpesvirus (KSHV), an oncogenic, human gamma-herpesvirus, is the etiological agent of Kaposi's Sarcoma the most common tumor of AIDS patients world-wide. KSHV is ...predominantly latent in the main KS tumor cell, the spindle cell, a cell of endothelial origin. KSHV modulates numerous host cell-signaling pathways to activate endothelial cells including major metabolic pathways involved in lipid metabolism. To identify the underlying cellular mechanisms of KSHV alteration of host signaling and endothelial cell activation, we identified changes in the host proteome, phosphoproteome and transcriptome landscape following KSHV infection of endothelial cells. A Steiner forest algorithm was used to integrate the global data sets and, together with transcriptome based predicted transcription factor activity, cellular networks altered by latent KSHV were predicted. Several interesting pathways were identified, including peroxisome biogenesis. To validate the predictions, we showed that KSHV latent infection increases the number of peroxisomes per cell. Additionally, proteins involved in peroxisomal lipid metabolism of very long chain fatty acids, including ABCD3 and ACOX1, are required for the survival of latently infected cells. In summary, novel cellular pathways altered during herpesvirus latency that could not be predicted by a single systems biology platform, were identified by integrated proteomics and transcriptomics data analysis and when correlated with our metabolomics data revealed that peroxisome lipid metabolism is essential for KSHV latent infection of endothelial cells.
Pathogenic variants in surfactant proteins SP-B and SP-C cause surfactant deficiency and interstitial lung disease. Surfactant proteins are synthesized as precursors (proSP-B, proSP-C), trafficked, ...and processed via a vesicular-regulated secretion pathway; however, control of vesicular trafficking events is not fully understood. Through the Undiagnosed Diseases Network, we evaluated a child with interstitial lung disease suggestive of surfactant deficiency. Variants in known surfactant dysfunction disorder genes were not found in trio exome sequencing. Instead, a de novo heterozygous variant in
was identified in the Ras/Rab GTPases family nucleotide binding domain, p.Asp136His. Functional studies were performed in
by knocking the proband variant into the conserved position (Asp135) of the ortholog,
Genetic analysis demonstrated that
Asp135His is damaging, producing a strong dominant negative gene product.
Asp135His heterozygotes were also defective in endocytosis and early endosome (EE) fusion. Immunostaining studies of the proband's lung biopsy revealed that RAB5B and EE marker EEA1 were significantly reduced in alveolar type II cells and that mature SP-B and SP-C were significantly reduced, while proSP-B and proSP-C were normal. Furthermore, staining normal lung showed colocalization of RAB5B and EEA1 with proSP-B and proSP-C. These findings indicate that dominant negative-acting RAB5B Asp136His and EE dysfunction cause a defect in processing/trafficking to produce mature SP-B and SP-C, resulting in interstitial lung disease, and that RAB5B and EEs normally function in the surfactant secretion pathway. Together, the data suggest a noncanonical function for RAB5B and identify
p.Asp136His as a genetic mechanism for a surfactant dysfunction disorder.
Variation in the preservation of β cell function in clinical trials in type 1 diabetes (T1D) has emphasized the need to define biomarkers to predict treatment response. The T1DAL trial targeted T ...cells with alefacept (LFA-3-Ig) and demonstrated C-peptide preservation in approximately 30% of new-onset T1D individuals. We analyzed islet antigen-reactive (IAR) CD4+ T cells in PBMC samples collected prior to treatment from alefacept- and placebo-treated individuals using flow cytometry and single-cell RNA sequencing. IAR CD4+ T cells at baseline had heterogeneous phenotypes. Transcript profiles formed phenotypic clusters of cells along a trajectory based on increasing maturation and activation, and T cell receptor (TCR) chains showed clonal expansion. Notably, the frequency of IAR CD4+ T cells with a memory phenotype and a unique transcript profile (cluster 3) were inversely correlated with C-peptide preservation in alefacept-treated, but not placebo-treated, individuals. Cluster 3 cells had a proinflammatory phenotype characterized by expression of the transcription factor BHLHE40 and the cytokines GM-CSF and TNF-α, and shared TCR chains with effector memory-like clusters. Our results suggest IAR CD4+ T cells as a potential baseline biomarker of response to therapies targeting the CD2 pathway and warrant investigation for other T cell-related therapies.
Human islet antigen reactive CD4+ memory T cells (IAR T cells) play a key role in the pathogenesis of autoimmune type 1 diabetes (T1D). Using single-cell RNA sequencing (scRNA-Seq) to identify T cell ...receptors (TCRs) in IAR T cells, we have identified a class of TCRs that share TCRα chains between individuals ("public" chains). We isolated IAR T cells from blood of healthy, new-onset T1D and established T1D donors using multiplexed CD154 enrichment and identified paired TCRαβ sequences from 2767 individual cells. More than a quarter of cells shared TCR junctions between 2 or more cells ("expanded"), and 29/47 (~62%) of expanded TCRs tested showed specificity for islet antigen epitopes. Public TCRs sharing TCRα junctions were most prominent in new-onset T1D. Public TCR sequences were more germline like than expanded unique, or "private," TCRs, and had shorter junction sequences, suggestive of fewer random nucleotide insertions. Public TCRα junctions were often paired with mismatched TCRβ junctions in TCRs; remarkably, a subset of these TCRs exhibited cross-reactivity toward distinct islet antigen peptides. Our findings demonstrate a prevalent population of IAR T cells with diverse specificities determined by TCRs with restricted TCRα junctions and germline-constrained antigen recognition properties. Since these "innate-like" TCRs differ from previously described immunodominant TCRβ chains in autoimmunity, they have implications for fundamental studies of disease mechanisms. Self-reactive restricted TCRα chains and their associated epitopes should be considered in fundamental and translational investigations of TCRs in T1D.
Therapeutics that inhibit IL-6 at different points in its signaling pathway are in clinical use, yet whether the immunological effects of these interventions differ based on their molecular target is ...unknown. We performed short-term interventions in individuals with type 1 diabetes using anti-IL-6 (siltuximab) or anti-IL-6 receptor (IL-6R; tocilizumab) therapies and investigated the impact of this in vivo blockade on T cell fate and function. Immune outcomes were influenced by the target of the therapeutic intervention (IL-6 versus IL-6R) and by peak drug concentration. Tocilizumab reduced ICOS expression on T follicular helper cell populations and T cell receptor-driven (TCR-driven) STAT3 phosphorylation. Siltuximab reversed resistance to Treg-mediated suppression and increased TCR-driven phosphorylated STAT3 and production of IL-10, IL-21, and IL-27 by T effectors. Together, these findings indicate that the context of IL-6 blockade in vivo drives distinct T cell-intrinsic changes that may influence therapeutic outcomes.
Recruitment of regulatory T cells (T
) to tumors is a hallmark of cancer progression. Tumor-derived factors, such as the cytokine thymic stromal lymphopoietin (TSLP), can influence T
function in ...tumors. In our study, we identified a subset of T
expressing the receptor for TSLP (TSLPR
T
) that were increased in colorectal tumors in humans and mice and largely absent in adjacent normal colon. This T
subset was also found in the peripheral blood of patients with colon cancer but not in the peripheral blood of healthy control subjects. Mechanistically, we found that this T
subset coexpressed the interleukin-33 (IL-33) receptor suppressor of tumorigenicity 2 (ST2) and had high programmed cell death 1 (PD-1) and cytotoxic lymphocyte-associated antigen 4 (CTLA-4) expression, regulated in part by the transcription factor Mef2c. T
-specific deletion of TSLPR, but not ST2, was associated with a reduction in tumor number and size with concomitant increase in T
1 cells in tumors in chemically induced mouse models of colorectal cancer. Therapeutic blockade of TSLP using TSLP-specific monoclonal antibodies effectively inhibited the progression of colorectal tumors in this mouse model. Collectively, these data suggest that TSLP controls the progression of colorectal cancer through regulation of tumor-specific T
function and represents a potential therapeutic target that requires further investigation.
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