Timing is everything: the regulation of type III secretion

Type Three Secretion Systems (T3SSs) are essential virulence determinants of many Gram-negative bacteria. The T3SS is an injection device that can transfer bacterial virulence proteins directly into host cells. The apparatus is made up of a basal body that spans both bacterial membranes and an extracellular needle that possesses a channel that is thought to act as a conduit for protein secretion. Contact with a host-cell membrane triggers the insertion of a pore into the target membrane, and effectors are translocated through this pore into the host cell. To assemble a functional T3SS, specific substrates must be targeted to the apparatus in the correct order. Recently, there have been many developments in our structural and functional understanding of the proteins involved in the regulation of secretion. Here we review the current understanding of protein components of the system thought to be involved in switching between different stages of secretion

SOX2 Co-Occupies Distal Enhancer Elements with Distinct POU Factors in ESCs and NPCs to Specify Cell State

SOX2 is a master regulator of both pluripotent embryonic stem cells (ESCs) and multipotent neural progenitor cells (NPCs); however, we currently lack a detailed understanding of how SOX2 controls these distinct stem cell populations. Here we show by genome-wide analysis that, while SOX2 bound to a distinct set of gene promoters in ESCs and NPCs, the majority of regions coincided with unique distal enhancer elements, important cis-acting regulators of tissue-specific gene expression programs. Notably, SOX2 bound the same consensus DNA motif in both cell types, suggesting that additional factors contribute to target specificity. We found that, similar to its association with OCT4 (Pou5f1) in ESCs, the related POU family member BRN2 (Pou3f2) co-occupied a large set of putative distal enhancers with SOX2 in NPCs. Forced expression of BRN2 in ESCs led to functional recruitment of SOX2 to a subset of NPC-specific targets and to precocious differentiation toward a neural-like state. Further analysis of the bound sequences revealed differences in the distances of SOX and POU peaks in the two cell types and identified motifs for additional transcription factors. Together, these data suggest that SOX2 controls a larger network of genes than previously anticipated through binding of distal enhancers and that transitions in POU partner factors may control tissue-specific transcriptional programs. Our findings have important implications for understanding lineage specification and somatic cell reprogramming, where SOX2, OCT4, and BRN2 have been shown to be key factors

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk

Three-dimensional quantification of myocardial perfusion during regadenoson stress computed tomography

BACKGROUND: There is no accepted methodology for CT-based vasodilator stress myocardial perfusion imaging and analysis. We developed a technique for quantitative 3D analysis of CT images, which provides several indices of myocardial perfusion. We sought to determine the ability of these indices during vasodilator stress to identify segments supplied by coronary arteries with obstructive disease and to test the accuracy of the detection of perfusion abnormalities against SPECT. METHODS: We studied 93 patients referred for CT coronary angiography (CTCA) who underwent regadenoson stress. 3D analysis of stress CT images yielded segmental perfusion indices: mean X-ray attenuation, severity of defect and relative defect volume. Each index was averaged for myocardial segments, grouped by severity of stenosis: 0%,70%. Objective detection of perfusion abnormalities was optimized in 47 patients and then independently tested in the remaining 46 patients. RESULTS: CTCA depicted normal coronary arteries or non-obstructive disease in 62 patients and stenosis of \u3e50% in 31. With increasing stenosis, segmental attenuation showed a 7% decrease, defect severity increased 11%, but relative defect volume was 7-fold higher in segments with obstructive disease (p50% showed sensitivity 0.78, specificity 0.54, accuracy 0.59. When compared to SPECT in a subset of 21 patients (14 with abnormal SPECT), stress CT perfusion analysis showed sensitivity 0.79, specificity 0.71, accuracy 0.76. CONCLUSIONS: 3D analysis of vasodilator stress CT images provides quantitative indices of myocardial perfusion, of which relative defect volume was most robust in identifying segments supplied by arteries with obstructive disease. This study may have implications on how CT stress perfusion imaging is performed and analyzed

BRN2 co-occupies distal enhancers with SOX2 in NPCs.

<p>(A) <i>de novo</i> MEME motif analysis of SOX2 bound regions in ESCs and NPCs revealed canonical SOX2 motif. (B) TRANSFAC BRN2 motifs enriched in SOX2 target regions in NPCs. p-values represent significance of enrichment based on Mann-Whitney Wilcoxon ranked sum test with Benjamini-Hochberg multiple hypothesis testing correction. (C) Heat maps of SOX2 and OCT4 at SOX2 bound promoters and enhancers centered on peaks of SOX2 enrichment and extended 4 kb in each direction. (D) Gene plots showing SOX2, OCT4, H3K4me1, and H3K27Ac density at the <i>Fbxo15</i> promoter and at poised enhancers of <i>Pax6</i> in ESCs. y-axis corresponds to reads per million. Genomic positions reflect NCBI Mouse Genome Build 36 (mm8). Gray boxes indicate regions co-occupied by SOX2 and OCT4. (E) Heatmaps of SOX2 and BRN2 enrichment at SOX2-bound promoters and enhancers in NPCs centered on peaks of SOX2 enrichment and extended 4 kb in each direction. (F) Gene plots showing SOX2, BRN2, H3K4me1, and H3K27Ac density at <i>Olig1</i> and <i>Ascl1</i> loci in NPCs. y-axis corresponds to reads per million. Due to the high enrichment of H3K27Ac at active promoters, y-axis was cut off to show full dynamic range of enhancer-associated H3K27Ac density. Genomic positions reflect NCBI Mouse Genome Build 36 (mm8). Gray boxes indicate regions of SOX2-BRN2 co-occupancy. * indicates known enhancer. (G) Breakdown of number of SOX2-BRN2 target enhancers that are H3K4me1+, H3K27Ac− (poised) or H3K4me1+/−, H3K27Ac+ (active). (H) Box and Violin plots representing expression data from Affymetrix arrays of genes linked to poised and active SOX2-BRN2 target enhancers in NPCs. y-axis corresponds to percentile expression rank, * denotes p-value<0.01, Student's T-test, two tailed. (I, J) GREAT analysis of genes linked to poised and active SOX2-BRN2 target enhancers in NPCs.</p

Additional transcription factor motifs are enriched in SOX2-POU-bound regions.

<p>(A) Heatmaps display the relationship between expression changes in transcription factors and the enrichment of their motifs in SOX2-BRN2 bound regions compared to SOX2-OCT4-bound regions. The full set of TRANSFAC motifs were ranked by statistical significance of enrichment in SOX2-BRN2-bound regions and in SOX2-OCT4-bound regions using the Mann-Whitney Wilcoxon test. The heat map on the right displays the change in rank of 108 TRANSFAC motifs between the two datasets. Only motifs that were ranked in the top 200 in either dataset are shown. The heat map on the left shows the fold change in gene expression between ESCs and NPCs of a transcription factor that recognizes the corresponding motif on the right. Scale bars: Left, fold gene expression change of transcription factors between ESCs (blue) and NPCs (yellow); Right, change in rank of TRANSFAC motifs between SOX2-OCT4 bound regions (blue) and SOX2-BRN2 bound regions (yellow). p-value reflects correlation of motif enrichment and gene expression of transcription factors which can recognize the motifs by a Monte-Carlo analysis. (B, C) Ingenuity Pathway Analysis to visualize the functional interconnection among genes associated with SOX2-BRN2 regions that also contain either an NF-I or RFX motif.</p