Analysis of the N-terminal region of human MLKL, as well as two distinct MLKL isoforms, reveals new insights into necroptotic cell death

© 2016 Authors. The pseudokinase mixed lineage kinase domain-like (MLKL) is an essential effector of necroptotic cell death. Two distinct human MLKL isoforms have previously been reported, but their capacities to trigger cell death have not been compared directly. Herein, we examine these two MLKL isoforms, and further probe the features of the human MLKL N-terminal domain that are required for cell death. Expression in HEK293T cells of the N-terminal 201 amino acids (aa) of human MLKL is sufficient to cause cell death, whereas expression of the first 154 aa is not. Given that aa 1125 are able to initiate necroptosis, our findings indicate that the helix that follows this region restrains necroptotic activity, which is again restored in longer constructs. Furthermore, MLKL isoform 2 (MLKL2), which lacks much of the regulatory pseudokinase domain, is a much more potent inducer of cell death than MLKL isoform 1 (MLKL1) in ectopic expression studies in HEK293T cells. Modelling predicts that a C-terminal helix constrains the activity of MLKL1, but not MLKL2. Although both isoforms are expressed by human monocyte-derived macrophages at the mRNA level, MLKL2 is expressed at much lower levels. We propose that it may have a regulatory role in controlling macrophage survival, either in the steady state or in response to specific stimuli

High-resolution longitudinal N- and O-glycoprofiling of human monocyte-to-macrophage transition.

Protein glycosylation impacts the development and function of innate immune cells. The glycophenotypes and the glycan remodelling associated with the maturation of macrophages from monocytic precursor populations remain incompletely described. Herein, label-free porous graphitised carbon-liquid chromatography-tandem mass spectrometry (PGC-LC-MS/MS) was employed to profile with high resolution the N- and O-glycome associated with human monocyte-to-macrophage transition. Primary blood-derived CD14+ monocytes were differentiated ex vivo in the absence of strong anti- and proinflammatory stimuli using a conventional 7-day granulocyte-macrophage colony-stimulating factor differentiation protocol with longitudinal sampling. Morphology and protein expression monitored by light microscopy and proteomics validated the maturation process. Glycomics demonstrated that monocytes and macrophages display similar N-glycome profiles, comprising predominantly paucimannosidic (Man1-3GlcNAc2Fuc0-1, 22.1-30.8%), oligomannosidic (Man5-9GlcNAc2, 29.8-35.7%) and α2,3/6-sialylated complex-type N-glycans with variable core fucosylation (27.6-39.1%). Glycopeptide analysis validated conjugation of these glycans to human proteins, while quantitative proteomics monitored the glycoenzyme expression levels during macrophage differentiation. Significant interperson glycome variations were observed suggesting a considerable physiology-dependent or heritable heterogeneity of CD14+ monocytes. Only few N-glycome changes correlated with the monocyte-to-macrophage transition across donors including decreased core fucosylation and reduced expression of mannose-terminating (paucimannosidic-/oligomannosidic-type) N-glycans in macrophages, while lectin flow cytometry indicated that more dramatic cell surface glycan remodelling occurs during maturation. The less heterogeneous core 1-rich O-glycome showed a minor decrease in core 2-type O-glycosylation but otherwise remained unchanged with macrophage maturation. This high-resolution glycome map underpinning normal monocyte-to-macrophage transition, the most detailed to date, aids our understanding of the molecular makeup pertaining to two vital innate immune cell types and forms an important reference for future glycoimmunological studies

High sensitivity and specificity of a 5-analyte protein and microRNA biosignature for identification of active tuberculosis.

Objectives: Non-sputum-based tests to accurately identify active tuberculosis (TB) disease and monitor response to therapy are urgently needed. This study examined the biomarker capacity of a panel of plasma proteins alone, and in conjunction with a previously identified miRNA signature, to identify active TB disease. Methods: The expression of nine proteins (IP-10, MCP-1, sTNFR1, RANTES, VEGF, IL-6, IL-10, TNF and Eotaxin) was measured in the plasma of 100 control subjects and 100 TB patients, at diagnosis (treatment naïve) and over the course of treatment (1-, 2- and 6-month intervals). The diagnostic performance of the nine proteins alone, and with the miRNA, was assessed. Results: Six proteins were significantly up-regulated in the plasma of TB patients at diagnosis compared to controls. Receiver operator characteristic curve analysis demonstrated that IP-10 with an AUC = 0.874, sensitivity of 75% and specificity of 87% was the best single biomarker candidate to distinguish TB patients from controls. IP-10 and IL-6 levels fell significantly within one month of commencing treatment and may have potential as indicators of a positive response to therapy. The combined protein and miRNA panel gave an AUC of 1.00. A smaller panel of only five analytes (IP-10, miR-29a, miR-146a, miR-99b and miR-221) showed an AUC = 0.995, sensitivity of 96% and specificity of 97%. Conclusions: A novel combination of miRNA and proteins significantly improves the sensitivity and specificity as a biosignature over single biomarker candidates and may be useful for the development of a non-sputum test to aid the diagnosis of active TB disease

The co-transcriptome of uropathogenic Escherichia coli-infected mouse macrophages reveals new insights into host-pathogen interactions

© 2014 The Authors. Cellular Microbiology published by John Wiley & Sons Ltd. Urinary tract infections (UTI) are among the most common infections in humans. Uropathogenic Escherichia coli (UPEC) can invade and replicate within bladder epithelial cells, and some UPEC strains can also survive within macrophages. To understand the UPEC transcriptional programme associated with intramacrophage survival, we performed host-pathogen co-transcriptome analyses using RNA sequencing. Mouse bone marrow-derived macrophages (BMMs) were challenged over a 24h time course with two UPEC reference strains that possess contrasting intramacrophage phenotypes: UTI89, which survives in BMMs, and 83972, which is killed by BMMs. Neither of these strains caused significant BMM cell death at the low multiplicity of infection that was used in this study. We developed an effective computational framework that simultaneously separated, annotated and quantified the mammalian and bacterial transcriptomes. Bone marrow-derived macrophages responded to the two UPEC strains with a broadly similar gene expression programme. In contrast, the transcriptional responses of the UPEC strains diverged markedly from each other. We identified UTI89 genes up-regulated at 24h post-infection, and hypothesized that some may contribute to intramacrophage survival. Indeed, we showed that deletion of one such gene (pspA) significantly reduced UTI89 survival within BMMs. Our study provides a technological framework for simultaneously capturing global changes at the transcriptional level in co-cultures, and has generated new insights into the mechanisms that UPEC use to persist within the intramacrophage environment

The role of multiple marks in epigenetic silencing and the emergence of a stable bivalent chromatin state

We introduce and analyze a minimal model of epigenetic silencing in budding yeast, built upon known biomolecular interactions in the system. Doing so, we identify the epigenetic marks essential for the bistability of epigenetic states. The model explicitly incorporates two key chromatin marks, namely H4K16 acetylation and H3K79 methylation, and explores whether the presence of multiple marks lead to a qualitatively different systems behavior. We find that having both modifications is important for the robustness of epigenetic silencing. Besides the silenced and transcriptionally active fate of chromatin, our model leads to a novel state with bivalent (i.e., both active and silencing) marks under certain perturbations (knock-out mutations, inhibition or enhancement of enzymatic activity). The bivalent state appears under several perturbations and is shown to result in patchy silencing. We also show that the titration effect, owing to a limited supply of silencing proteins, can result in counter-intuitive responses. The design principles of the silencing system is systematically investigated and disparate experimental observations are assessed within a single theoretical framework. Specifically, we discuss the behavior of Sir protein recruitment, spreading and stability of silenced regions in commonly-studied mutants (e.g., sas2, dot1) illuminating the controversial role of Dot1 in the systems biology of yeast silencing.Comment: Supplementary Material, 14 page

Frequency-specific hippocampal-prefrontal interactions during associative learning

Much of our knowledge of the world depends on learning associations (for example, face-name), for which the hippocampus (HPC) and prefrontal cortex (PFC) are critical. HPC-PFC interactions have rarely been studied in monkeys, whose cognitive and mnemonic abilities are akin to those of humans. We found functional differences and frequency-specific interactions between HPC and PFC of monkeys learning object pair associations, an animal model of human explicit memory. PFC spiking activity reflected learning in parallel with behavioral performance, whereas HPC neurons reflected feedback about whether trial-and-error guesses were correct or incorrect. Theta-band HPC-PFC synchrony was stronger after errors, was driven primarily by PFC to HPC directional influences and decreased with learning. In contrast, alpha/beta-band synchrony was stronger after correct trials, was driven more by HPC and increased with learning. Rapid object associative learning may occur in PFC, whereas HPC may guide neocortical plasticity by signaling success or failure via oscillatory synchrony in different frequency bands.National Institute of Mental Health (U.S.) (Conte Center Grant P50-MH094263-03)National Institute of Mental Health (U.S.) (Fellowship F32-MH081507)Picower Foundatio

Developing new TB biomarkers, are miRNA the answer?

© 2019 Elsevier Ltd Efforts to reduce the global TB burden are hindered by the lack of simple, reliable non-sputum based diagnostics. To date studies investigating the biomarker potential of circulating host proteins and mRNA have not shown sufficient diagnostic utility. Recently, there has been increasing interest in circulating miRNA as a biomarker of TB disease. This review examined all published miRNA-TB biomarker studies to determine if a reproducible miRNA signature of TB disease could be elucidated. From 15 miRNA profiling studies, 894 miRNA differentially expressed between TB patients and healthy controls were identified in at least one study. Of these, 143 miRNA were validated by qPCR with 53 differentially expressed between TB patients and controls. Interestingly, only 8 of these miRNA were identified in 2 or more studies, and no consensus on a reproducible miRNA signature for identification of TB disease could be identified. TB disease is clearly associated with a wide breadth of differentially expressed miRNA. This review highlights our recent progress and the multiple factors, including environment, source of tissue, ethnicity and extent of TB disease that may influence miRNA expression. Coordinated efforts are required to validate identified targets in multiple populations to progress miRNA biomarker development

Co-transcriptomic analysis by rna sequencing to simultaneously measure regulated gene expression in host and bacterial pathogen

© Springer Science+Business Media New York 2016. Intramacrophage pathogens subvert antimicrobial defence pathways using various mechanisms, including the targeting of host TLR-mediated transcriptional responses. Conversely, TLR-inducible host defence mechanisms subject intramacrophage pathogens to stress, thus altering pathogen gene expression programs. Important biological insights can thus be gained through the analysis of gene expression changes in both the host and the pathogen during an infection. Traditionally, research methods have involved the use of qPCR, microarrays and/or RNA sequencing to identify transcriptional changes in either the host or the pathogen. Here we describe the application of RNA sequencing using samples obtained from in vitro infection assays to simultaneously quantify both host and bacterial pathogen gene expression changes, as well as general approaches that can be undertaken to interpret the RNA sequencing data that is generated. These methods can be used to provide insights into host TLR-regulated transcriptional responses to microbial challenge, as well as pathogen subversion mechanisms against such responses

A transcriptional blood signature distinguishes early tuberculosis disease from latent tuberculosis infection and uninfected individuals in a Vietnamese cohort.

OBJECTIVES:Global tuberculosis (TB) control is restricted by the failure to detect an estimated 3.3 million TB cases annually. In the majority of TB endemic settings, sputum smear microscopy is used to diagnose TB, but this test is insensitive for TB in its early stages. The objective of this study is to establish a concise gene signature that discriminates between individuals with early TB disease, latent TB infection (LTBI) and those without infection. METHODS:This is a case control study nested within a cluster-randomised trial of population screening for active TB using Xpert MTB/RIF. Whole blood samples from 303 participants with active TB (97), LTBI (92) and uninfected individuals (114) were subject to transcriptomic analysis of selected target genes based on a systematic review of previous studies. RESULTS:Analysis of 82 genes identified a pattern of differentially expressed genes in TB disease. A seven gene signature was identified that distinguished between TB disease and no TB disease with an AUC of 0.86 (95% CI: 0.80-0.91), and between TB disease from LTBI with an AUC of 0.88 (95% CI: 0.82-0.93). CONCLUSION:This gene signature accurately distinguishes early TB disease from those without TB disease or infection, in the context of community-wide TB screening. It could be used as a non-sputum based screening tool or triage test to detect prevalent cases of TB in the community