Noncoding mutations cause super-enhancer retargeting resulting in protein synthesis dysregulation during B cell lymphoma progression.

Whole-genome sequencing of longitudinal tumor pairs representing transformation of follicular lymphoma to high-grade B cell lymphoma with MYC and BCL2 rearrangements (double-hit lymphoma) identified coding and noncoding genomic alterations acquired during lymphoma progression. Many of these transformation-associated alterations recurrently and focally occur at topologically associating domain resident regulatory DNA elements, including H3K4me3 promoter marks located within H3K27ac super-enhancer clusters in B cell non-Hodgkin lymphoma. One region found to undergo recurrent alteration upon transformation overlaps a super-enhancer affecting the expression of the PAX5/ZCCHC7 gene pair. ZCCHC7 encodes a subunit of the Trf4/5-Air1/2-Mtr4 polyadenylation-like complex and demonstrated copy number gain, chromosomal translocation and enhancer retargeting-mediated transcriptional upregulation upon lymphoma transformation. Consequently, lymphoma cells demonstrate nucleolar dysregulation via altered noncoding 5.8S ribosomal RNA processing. We find that a noncoding mutation acquired during lymphoma progression affects noncoding rRNA processing, thereby rewiring protein synthesis leading to oncogenic changes in the lymphoma proteome.

Segmental analysis of liver cirrhosis with different etiologies: a study based on iodine mixed imaging in port-venous phase.

BACKGROUND: Computed tomography (CT) in port-venous phase can display the intra-hepatic vessels, and may provide the possibility for segment function evaluation for cirrhosis. PURPOSE: To assess the value of iodine mixed imaging of dual-source dual-energy CT in port-venous phase in segmental evaluation of liver cirrhosis with different etiologies. MATERIAL AND METHODS: Patients diagnosed with liver cirrhosis were enrolled. Patients without cirrhosis were included as a control group. Each patient underwent iodine-contrast enhanced multi-phase dual-energy CT scanning. Parameters were analyzed by SPSS, version 22.0, and Medcalc. RESULTS: In total, 256 patients were investigated, including 114 Child-Pugh A, 51 Child-Pugh B, 41 Child-Pugh C and 50 control patients. Total iodine content (ICt)/body surface area (BSA) in the cirrhosis group was significantly lower than the control group (P < 0.05) and the standardized-iodine parameter (SI) of each segment decreased with cirrhosis progression. In Child-Pugh A and B, SI increased more significantly in the caudal and lateral segment in A (alcholism) than in the V (virus-related) and N (non-alcoholic steatohepatitis) groups (P < 0.001). ICt/BSA showed the best diagnosis power of cirrhosis with an area under the curve of 0.765, sensitivity of 76.0% and specificity of 71.8%. CONCLUSION: Blood flow compensated in the left lateral and caudal lobe in the early stage of liver cirrhosis. The compensation in alcoholism in the middle and early stages is significantly higher than that of V and N cirrhosis. Iodine mixed imaging in portal phase may provide the possibility of an incremental value in segmented blood flow perfusion and functional evaluation of liver cirrhosis on a morphological basis.

m6A RNA modification regulates innate lymphoid cell responses in a lineage-specific manner.

Innate lymphoid cells (ILCs) can quickly switch from a quiescent state to an active state and rapidly produce effector molecules that provide critical early immune protection. How the post-transcriptional machinery processes different stimuli and initiates robust gene expression in ILCs is poorly understood. Here, we show that deletion of the N6-methyladenosine (m6A) writer protein METTL3 has little impact on ILC homeostasis or cytokine-induced ILC1 or ILC3 responses but significantly diminishes ILC2 proliferation, migration and effector cytokine production and results in impaired antihelminth immunity. m6A RNA modification supports an increase in cell size and transcriptional activity in activated ILC2s but not in ILC1s or ILC3s. Among other transcripts, the gene encoding the transcription factor GATA3 is highly m6A methylated in ILC2s. Targeted m6A demethylation destabilizes nascent Gata3 mRNA and abolishes the upregulation of GATA3 and ILC2 activation. Our study suggests a lineage-specific requirement of m6A for ILC2 responses.

Diagnostic potential of myocardial early systolic lengthening for patients with suspected non-ST-segment elevation acute coronary syndrome.

BACKGROUND: During early systole, ischemic myocardium with reduced active force experiences early systolic lengthening (ESL). This study aimed to explore the diagnostic potential of myocardial ESL in suspected non-ST-segment elevation acute coronary syndrome (NSTE-ACS) patients with normal wall motion and left ventricular ejection fraction (LVEF). METHODS: Overall, 195 suspected NSTE-ACS patients with normal wall motion and LVEF, who underwent speckle tracking echocardiography (STE) before coronary angiography, were included in this study. Patients were stratified into the coronary artery disease (CAD) group when there was ≥ 50% stenosis in at least one major coronary artery. The CAD patients were further stratified into the significant (≥ 70% reduction of vessel diameter) stenosis group or the nonsignificant stenosis group. Myocardial strain parameters, including global longitudinal strain (GLS), duration of early systolic lengthening (DESL), early systolic index (ESI), and post-systolic index (PSI), were analyzed using STE and compared between groups. Receiver operating characteristic curve (ROC) analysis was performed to determine the diagnostic accuracy. Logistic regression analysis was conducted to establish the independent and incremental determinants for the presence of significant coronary stenosis. RESULTS: The DESL and ESI values were higher in patients with CAD than those without CAD. In addition, CAD patients with significant coronary stenosis had higher DESL and ESI than those without significant coronary stenosis. The ROC analysis revealed that ESI was superior to PSI for identifying patients with CAD, and further superior to GLS and PSI for predicting significant coronary stenosis. Moreover, ESI could independently and incrementally predict significant coronary stenosis in patients with CAD. CONCLUSIONS: The myocardial ESI is of great value for the diagnosis and risk stratification of clinically suspected NSTE-ACS patients with normal LVEF and wall motion.

Specific regulation of BACH1 by the hotspot mutant p53R175H reveals a distinct gain-of-function mechanism.

Although the gain of function (GOF) of p53 mutants is well recognized, it remains unclear whether different p53 mutants share the same cofactors to induce GOFs. In a proteomic screen, we identified BACH1 as a cellular factor that recognizes the p53 DNA-binding domain depending on its mutation status. BACH1 strongly interacts with p53R175H but fails to effectively bind wild-type p53 or other hotspot mutants in vivo for functional regulation. Notably, p53R175H acts as a repressor for ferroptosis by abrogating BACH1-mediated downregulation of SLC7A11 to enhance tumor growth; conversely, p53R175H promotes BACH1-dependent tumor metastasis by upregulating expression of pro-metastatic targets. Mechanistically, p53R175H-mediated bidirectional regulation of BACH1 function is dependent on its ability to recruit the histone demethylase LSD2 to target promoters and differentially modulate transcription. These data demonstrate that BACH1 acts as a unique partner for p53R175H in executing its specific GOFs and suggest that different p53 mutants induce their GOFs through distinct mechanisms.

RNA exosome drives early B cell development via noncoding RNA processing mechanisms.

B cell development is linked to successful V(D)J recombination, allowing B cell receptor expression and ultimately antibody secretion for adaptive immunity. Germline noncoding RNAs (ncRNAs) are produced at immunoglobulin (Ig) loci during V(D)J recombination, but their function and posttranscriptional regulation are incompletely understood. Patients with trichohepatoenteric syndrome, characterized by RNA exosome pathway component mutations, exhibit lymphopenia, thus demonstrating the importance of ncRNA surveillance in B cell development in humans. To understand the role of RNA exosome in early B cell development in greater detail, we generated mouse models harboring a B cell-specific cre allele (Mb1cre), coupled to conditional inversion-deletion alleles of one RNA exosome core component (Exosc3) or RNase catalytic subunits (Exosc10 or Dis3). We noticed increased expression of RNA exosome subunits during V(D)J recombination, whereas a B cell developmental blockade at the pro-B cell stage was observed in the different knockout mice, overlapping with a lack of productive rearrangements of VDJ genes at the Ig heavy chain (Igh). This unsuccessful recombination prevented differentiation into pre-B cells, with accumulation of ncRNAs and up-regulation of the p53 pathway. Introduction of a prearranged Igh VDJ allele partly rescued the pre-B cell population in Dis3-deficient cells, although V-J recombination defects were observed at Ig light chain kappa (Igκ), preventing subsequent B cell development. These observations demonstrated that the RNA exosome complex is important for Igh and Igκ recombination and establish the relevance of RNA processing for optimal diversification at these loci during B cell development.

Mechanism of noncoding RNA-associated N6-methyladenosine recognition by an RNA processing complex during IgH DNA recombination.

Immunoglobulin heavy chain (IgH) locus-associated G-rich long noncoding RNA (SµGLT) is important for physiological and pathological B cell DNA recombination. We demonstrate that the METTL3 enzyme-catalyzed N6-methyladenosine (m6A) RNA modification drives recognition and 3' end processing of SµGLT by the RNA exosome, promoting class switch recombination (CSR) and suppressing chromosomal translocations. The recognition is driven by interaction of the MPP6 adaptor protein with nuclear m6A reader YTHDC1. MPP6 and YTHDC1 promote CSR by recruiting AID and the RNA exosome to actively transcribe SµGLT. Direct suppression of m6A modification of SµGLT or of m6A reader YTHDC1 reduces CSR. Moreover, METTL3, an essential gene for B cell development in the bone marrow and germinal center, suppresses IgH-associated aberrant DNA breaks and prevents genomic instability. Taken together, we propose coordinated and central roles for MPP6, m6A modification, and m6A reader proteins in controlling long noncoding RNA processing, DNA recombination, and development in B cells.

A ChIP-exo screen of 887 Protein Capture Reagents Program transcription factor antibodies in human cells.

Antibodies offer a powerful means to interrogate specific proteins in a complex milieu. However, antibody availability and reliability can be problematic, whereas epitope tagging can be impractical in many cases. To address these limitations, the Protein Capture Reagents Program (PCRP) generated over a thousand renewable monoclonal antibodies (mAbs) against human presumptive chromatin proteins. However, these reagents have not been widely field-tested. We therefore performed a screen to test their ability to enrich genomic regions via chromatin immunoprecipitation (ChIP) and a variety of orthogonal assays. Eight hundred eighty-seven unique antibodies against 681 unique human transcription factors (TFs) were assayed by ultra-high-resolution ChIP-exo/seq, generating approximately 1200 ChIP-exo data sets, primarily in a single pass in one cell type (K562). Subsets of PCRP mAbs were further tested in ChIP-seq, CUT&RUN, STORM super-resolution microscopy, immunoblots, and protein binding microarray (PBM) experiments. About 5% of the tested antibodies displayed high-confidence target (i.e., cognate antigen) enrichment across at least one assay and are strong candidates for additional validation. An additional 34% produced ChIP-exo data that were distinct from background and thus warrant further testing. The remaining 61% were not substantially different from background, and likely require consideration of a much broader survey of cell types and/or assay optimizations. We show and discuss the metrics and challenges to antibody validation in chromatin-based assays.

Proteasomal Regulation of Mammalian SPT16 in Controlling Transcription.

FACT (facilitates chromatin transcription), an essential and evolutionarily conserved heterodimer from yeast to humans, controls transcription and is found to be upregulated in various cancers. However, the basis for such upregulation is not clearly understood. Our recent results deciphering a new ubiquitin-proteasome system regulation of the FACT subunit SPT16 in orchestrating transcription in yeast hint at the involvement of the proteasome in controlling FACT in humans, with a link to cancer. To test this, we carried out experiments in human embryonic kidney (HEK293) cells, which revealed that human SPT16 undergoes ubiquitylation and that its abundance is increased following inhibition of the proteolytic activity of the proteasome, thus implying proteasomal regulation of human SPT16. Furthermore, we find that the increased abundance/expression of SPT16 in HEK293 cells alters the transcription of genes, including ones associated with cancer, and that the proteasomal degradation of SPT16 is impaired in kidney cancer (Caki-2) cells to upregulate SPT16. Like human SPT16, murine SPT16 in C2C12 cells also undergoes ubiquitylation and proteasomal degradation to regulate transcription. Collectively, our results reveal a proteasomal regulation of mammalian SPT16, with physiological relevance in controlling transcription, and implicate such proteasomal control in the upregulation of SPT16 in cancer.

Noncoding RNA processing by DIS3 regulates chromosomal architecture and somatic hypermutation in B cells.

Noncoding RNAs are exquisitely titrated by the cellular RNA surveillance machinery for regulating diverse biological processes. The RNA exosome, the predominant 3' RNA exoribonuclease in mammalian cells, is composed of nine core and two catalytic subunits. Here, we developed a mouse model with a conditional allele to study the RNA exosome catalytic subunit DIS3. In DIS3-deficient B cells, integrity of the immunoglobulin heavy chain (Igh) locus in its topologically associating domain is affected, with accumulation of DNA-associated RNAs flanking CTCF-binding elements, decreased CTCF binding to CTCF-binding elements and disorganized cohesin localization. DIS3-deficient B cells also accumulate activation-induced cytidine deaminase-mediated asymmetric nicks, altering somatic hypermutation patterns and increasing microhomology-mediated end-joining DNA repair. Altered mutation patterns and Igh architectural defects in DIS3-deficient B cells lead to decreased class-switch recombination but increased chromosomal translocations. Our observations of DIS3-mediated architectural regulation at the Igh locus are reflected genome wide, thus providing evidence that noncoding RNA processing is an important mechanism for controlling genome organization.

Noncoding RNA transcription alters chromosomal topology to promote isotype-specific class switch recombination.

B cells undergo two types of genomic alterations to increase antibody diversity: introduction of point mutations into immunoglobulin heavy- and light-chain (IgH and IgL) variable regions by somatic hypermutation (SHM) and alteration of antibody effector functions by changing the expressed IgH constant region exons through IgH class switch recombination (CSR). SHM and CSR require the B cell-specific activation-induced cytidine deaminase (AID) protein, the transcription of germline noncoding RNAs, and the activity of the 3' regulatory region (3'RR) super-enhancer. Although many transcription regulatory elements (e.g., promoters and enhancers) reside inside the IgH and IgL sequences, the question remains whether clusters of regulatory elements outside IgH control CSR. Using RNA exosome-deficient mouse B cells where long noncoding RNAs (lncRNAs) are easily detected, we identified a cluster of three RNA-expressing elements that includes lncCSRIgA (that expresses lncRNA-CSRIgA). B cells isolated from a mouse model lacking lncRNA-CSRIgA transcription fail to undergo normal levels of CSR to IgA both in B cells of the Peyer's patches and grown in ex vivo culture conditions. lncRNA-CSRIgA is expressed from an enhancer site (lncCSRIgA ) to facilitate the recruitment of regulatory proteins to a nearby CTCF site (CTCFlncCSR) that alters the chromosomal interactions inside the TADlncCSRIgA and long-range interactions with the 3'RR super-enhancer. Humans with IgA deficiency show polymorphisms in the lncCSRIgA locus compared with the normal population. Thus, we provide evidence for an evolutionarily conserved topologically associated domain (TADlncCSRIgA) that coordinates IgA CSR in Peyer's patch B cells through an lncRNA (lncRNA-CSRIgA) transcription-dependent mechanism.

3D Modeling of Esophageal Development using Human PSC-Derived Basal Progenitors Reveals a Critical Role for Notch Signaling.

Pluripotent stem cells (PSCs) could provide a powerful system to model development of the human esophagus, whose distinct tissue organization compared to rodent esophagus suggests that developmental mechanisms may not be conserved between species. We therefore established an efficient protocol for generating esophageal progenitor cells (EPCs) from human PSCs. We found that inhibition of TGF-ß and BMP signaling is required for sequential specification of EPCs, which can be further purified using cell-surface markers. These EPCs resemble their human fetal counterparts and can recapitulate normal development of esophageal stratified squamous epithelium during in vitro 3D cultures and in vivo. Importantly, combining hPSC differentiation strategies with mouse genetics elucidated a critical role for Notch signaling in the formation of this epithelium. These studies therefore not only provide an efficient approach to generate EPCs, but also offer a model system to study the regulatory mechanisms underlying development of the human esophagus.

Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors.

The origin and specification of human dendritic cells (DCs) have not been investigated at the clonal level. Through the use of clonal assays, combined with statistical computation, to quantify the yield of granulocytes, monocytes, lymphocytes and three subsets of DCs from single human CD34+ progenitor cells, we found that specification to the DC lineage occurred in parallel with specification of hematopoietic stem cells (HSCs) to the myeloid and lymphoid lineages. This started as a lineage bias defined by specific transcriptional programs that correlated with the combinatorial 'dose' of the transcription factors IRF8 and PU.1, which was transmitted to most progeny cells and was reinforced by upregulation of IRF8 expression driven by the hematopoietic cytokine FLT3L during cell division. We propose a model in which specification to the DC lineage is driven by parallel and inheritable transcriptional programs in HSCs and is reinforced over cell division by recursive interactions between transcriptional programs and extrinsic signals.

Nuclear Proximity of Mtr4 to RNA Exosome Restricts DNA Mutational Asymmetry.

The distribution of sense and antisense strand DNA mutations on transcribed duplex DNA contributes to the development of immune and neural systems along with the progression of cancer. Because developmentally matured B cells undergo biologically programmed strand-specific DNA mutagenesis at focal DNA/RNA hybrid structures, they make a convenient system to investigate strand-specific mutagenesis mechanisms. We demonstrate that the sense and antisense strand DNA mutagenesis at the immunoglobulin heavy chain locus and some other regions of the B cell genome depends upon localized RNA processing protein complex formation in the nucleus. Both the physical proximity and coupled activities of RNA helicase Mtr4 (and senataxin) with the noncoding RNA processing function of RNA exosome determine the strand-specific distribution of DNA mutations. Our study suggests that strand-specific DNA mutagenesis-associated mechanisms will play major roles in other undiscovered aspects of organismic development.

Electrospun Nanofibres Containing Antimicrobial Plant Extracts.

Over the last 10 years great research interest has been directed toward nanofibrous architectures produced by electrospinning bioactive plant extracts. The resulting structures possess antimicrobial, anti-inflammatory, and anti-oxidant activity, which are attractive for biomedical applications and food industry. This review describes the diverse approaches that have been developed to produce electrospun nanofibres that are able to deliver naturally-derived chemical compounds in a controlled way and to prevent their degradation. The efficacy of those composite nanofibres as wound dressings, scaffolds for tissue engineering, and active food packaging systems will be discussed.

Discovering a critical transition state from nonalcoholic hepatosteatosis to nonalcoholic steatohepatitis by lipidomics and dynamical network biomarkers.

Nonalcoholic fatty liver disease (NAFLD) is a major risk factor for type 2 diabetes and metabolic syndrome. However, accurately differentiating nonalcoholic steatohepatitis (NASH) from hepatosteatosis remains a clinical challenge. We identified a critical transition stage (termed pre-NASH) during the progression from hepatosteatosis to NASH in a mouse model of high fat-induced NAFLD, using lipidomics and a mathematical model termed dynamic network biomarkers (DNB). Different from the conventional biomarker approach based on the abundance of molecular expressions, the DNB model exploits collective fluctuations and correlations of different metabolites at a network level. We found that the correlations between the blood and liver lipid species drastically decreased after the transition from steatosis to NASH, which may account for the current difficulty in differentiating NASH from steatosis based on blood lipids. Furthermore, most DNB members in the blood circulation, especially for triacylglycerol (TAG), are also identified in the liver during the disease progression, suggesting a potential clinical application of DNB to diagnose NASH based on blood lipids. We further identified metabolic pathways responsible for this transition. Our study suggests that the transition from steatosis to NASH is not smooth and the existence of pre-NASH may be partially responsible for the current clinical limitations to diagnose NASH. If validated in humans, our study will open a new avenue to reliably diagnose pre-NASH and achieve early intervention of NAFLD.

Big-data-based edge biomarkers: study on dynamical drug sensitivity and resistance in individuals.

Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically 'small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as 'large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression data from a malaria vaccine trial by big-data-based edge biomarkers from module network rewiring-analysis. The illustrative results show that the identified module biomarkers can accurately distinguish vaccines with or without protection and outperformed previous reported gene signatures in terms of effectiveness and efficiency.

Diagnosing phenotypes of single-sample individuals by edge biomarkers.

Network or edge biomarkers are a reliable form to characterize phenotypes or diseases. However, obtaining edges or correlations between molecules for an individual requires measurement of multiple samples of that individual, which are generally unavailable in clinical practice. Thus, it is strongly demanded to diagnose a disease by edge or network biomarkers in one-sample-for-one-individual context. Here, we developed a new computational framework, EdgeBiomarker, to integrate edge and node biomarkers to diagnose phenotype of each single test sample. By applying the method to datasets of lung and breast cancer, it reveals new marker genes/gene-pairs and related sub-networks for distinguishing earlier and advanced cancer stages. Our method shows advantages over traditional methods: (i) edge biomarkers extracted from non-differentially expressed genes achieve better cross-validation accuracy of diagnosis than molecule or node biomarkers from differentially expressed genes, suggesting that certain pathogenic information is only present at the level of network and under-estimated by traditional methods; (ii) edge biomarkers categorize patients into low/high survival rate in a more reliable manner; (iii) edge biomarkers are significantly enriched in relevant biological functions or pathways, implying that the association changes in a network, rather than expression changes in individual molecules, tend to be causally related to cancer development. The new framework of edge biomarkers paves the way for diagnosing diseases and analyzing their molecular mechanisms by edges or networks in one-sample-for-one-individual basis. This also provides a powerful tool for precision medicine or big-data medicine.

Edge biomarkers for classification and prediction of phenotypes.

In general, a disease manifests not from malfunction of individual molecules but from failure of the relevant system or network, which can be considered as a set of interactions or edges among molecules. Thus, instead of individual molecules, networks or edges are stable forms to reliably characterize complex diseases. This paper reviews both traditional node biomarkers and edge biomarkers, which have been newly proposed. These biomarkers are classified in terms of their contained information. In particular, we show that edge and network biomarkers provide novel ways of stably and reliably diagnosing the disease state of a sample. First, we categorize the biomarkers based on the information used in the learning and prediction steps. We then briefly introduce conventional node biomarkers, or molecular biomarkers without network information, and their computational approaches. The main focus of this paper is edge and network biomarkers, which exploit network information to improve the accuracy of diagnosis and prognosis. Moreover, by extracting both network and dynamic information from the data, we can develop dynamical network and edge biomarkers. These biomarkers not only diagnose the immediate pre-disease state but also detect the critical molecules or networks by which the biological system progresses from the healthy to the disease state. The identified critical molecules can be used as drug targets, and the critical state indicates the critical point of disease control. The paper also discusses representative biomarker-based methods.