RNA-binding proteins in eye development and disease: implication of conserved RNA granule components

The molecular biology of metazoan eye development is an area of intense investigation. These efforts have led to the surprising recognition that although insect and vertebrate eyes have dramatically different structures, the orthologs or family members of several conserved transcription and signaling regulators such as Pax6, Six3, Prox1, and Bmp4 are commonly required for their development. In contrast, our understanding of posttranscriptional regulation in eye development and disease, particularly regarding the function of RNA-binding proteins (RBPs), is limited. We examine the present knowledge of RBPs in eye development in the insect model Drosophila as well as several vertebrate models such as fish, frog, chicken, and mouse. Interestingly, of the 42 RBPs that have been investigated for their expression or function in vertebrate eye development, 24 (~60%) are recognized in eukaryotic cells as components of RNA granules such as processing bodies, stress granules, or other specialized ribonucleoprotein (RNP) complexes. We discuss the distinct developmental and cellular events that may necessitate potential RBP/RNA granule-associated RNA regulon models to facilitate posttranscriptional control of gene expression in eye morphogenesis. In support of these hypotheses, three RBPs and RNP/RNA granule components Tdrd7, Caprin2, and Stau2 are linked to ocular developmental defects such as congenital cataract, Peters anomaly, and microphthalmia in human patients or animal models. We conclude by discussing the utility of interdisciplinary approaches such as the bioinformatics tool iSyTE (integrated Systems Tool for Eye gene discovery) to prioritize RBPs for deriving posttranscriptional regulatory networks in eye development and disease. WIREs RNA 2016, 7:527-557. doi: 10.1002/wrna.1355 For further resources related to this article, please visit the WIREs website

Comparison of diagnostic accuracy of early screening for pre-eclampsia by NICE guidelines and a method combining maternal factors and biomarkers: results of SPREE

Objective To test the hypothesis that the performance of first-trimester screening for pre-eclampsia (PE) by a method that uses Bayes’ theorem to combine maternal factors with biomarkers is superior to that defined by current National Institute for Health and Care Excellence (NICE) guidelines. Methods This was a prospective multicenter study (screening program for pre-eclampsia (SPREE)) in seven National Health Service maternity hospitals in England, of women recruited between April and December 2016. Singleton pregnancies at 11–13weeks’ gestation had recording of maternal characteristics and medical history and measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), serum placental growth factor (PlGF) and serum pregnancy-associated plasma protein-A (PAPP-A). The performance of screening for PE by the Bayes’ theorem-based method was compared with that of the NICE method. Primary comparison was detection rate (DR) using NICE method vs mini-combined test (maternal factors, MAP and PAPP-A) in the prediction of PE at any gestational age (all-PE) for the same screen-positive rate determined by the NICE method. Key secondary comparisons were DR of screening recommended by the NICE guidelines vs three Bayes’ theorem-based methods (maternal factors, MAP and PAPP-A; maternal factors, MAP and PlGF; and maternal factors, MAP, UtA-PI and PlGF) in the prediction of preterm PE, defined as that requiring delivery <37 weeks. Results All-PE developed in 473 (2.8%) of the 16 747 pregnancies and preterm PE developed in 142 (0.8%). The screen-positive rate by the NICE method was 10.3% and the DR for all-PE was 30.4% and for preterm PE it was 40.8%. Compliance with the NICE recommendation that women at high risk for PE should be treated with aspirin from the first trimester to the end of pregnancy was only 23%. The DR of the mini-combined test for all-PE was 42.5%, which was superior to that of the NICE method by 12.1% (95% CI, 7.9–16.2%). In screening for preterm PE by a combination of maternal factors, MAP and PlGF, the DR was 69.0%, which was superior to that of the NICE method by 28.2% (95% CI, 19.4–37.0%) and with the addition of UtA-PI the DR was 82.4%, which was higher than that of the NICE method by 41.6% (95% CI, 33.2–49.9%). Conclusions The performance of screening for PE as currently recommended by NICE guidelines is poor and compliance with these guidelines is low. The performance of screening is substantially improved by a method combining maternal factors with biomarkers

Granzyme A-producing T helper cells are critical for acute graft-versus-host disease

Acute graft-versus-host disease (aGVHD) can occur after hematopoietic cell transplant in patients undergoing treatment for hematological malignancies or inborn errors. Although CD4+ T helper (Th) cells play a major role in aGVHD, the mechanisms by which they contribute, particularly within the intestines, have remained elusive. We have identified a potentially novel subset of Th cells that accumulated in the intestines and produced the serine protease granzyme A (GrA). GrA+ Th cells were distinct from other Th lineages and exhibited a noncytolytic phenotype. In vitro, GrA+ Th cells differentiated in the presence of IL-4, IL-6, and IL-21 and were transcriptionally unique from cells cultured with either IL-4 or the IL-6/IL-21 combination alone. In vivo, both STAT3 and STAT6 were required for GrA+ Th cell differentiation and played roles in maintenance of the lineage identity. Importantly, GrA+ Th cells promoted aGVHD-associated morbidity and mortality and contributed to crypt destruction within intestines but were not required for the beneficial graft-versus-leukemia effect. Our data indicate that GrA+ Th cells represent a distinct Th subset and are critical mediators of aGVHD

Retrospective observational RT-PCR analyses on 688 babies born to 843 SARS-CoV-2 positive mothers, placental analyses and diagnostic analyses limitations suggest vertical transmission is possible

Research question: Is there vertical transmission (from mother to baby antenatally or intrapartum) after SARS-CoV-2 (COVID-19) infected pregnancy? Study design: A systematic search related to SARS-CoV-2 (COVID-19), pregnancy, neonatal complications, viral and vertical transmission. The duration was from December 2019 to May 2020. Results: A total of 84 studies with 862 COVID positive women were included. Two studies had ongoing pregnancies while 82 studies included 705 babies, 1 miscarriage and 1 medical termination of pregnancy (MTOP). Most publications (50/84, 59.5%), reported small numbers (&lt;5) of positive babies. From 75 studies, 18 babies were COVID-19 positive. The first reverse transcription polymerase chain reaction (RT-PCR) diagnostic test was done in 449 babies and 2 losses, 2nd RT-PCR was done in 82 babies, IgM tests were done in 28 babies, and IgG tests were done in 28 babies. On the first RT-PCR, 47 studies reported time of testing while 28 studies did not. Positive results in the first RT-PCR were seen in 14 babies. Earliest tested at birth and the average time of the result was 22 hours. Three babies with negative first RT-PCR became positive on the second RT-PCR at day 6, day 7 and at 24 hours which continued to be positive at 1 week. Four studies with a total of 4 placental swabs were positive demonstrating SARS-CoV-2 localised in the placenta. In 2 studies, 10 tests for amniotic fluid were positive for SARS-CoV-2. These 2 babies were found to be positive on RT-PCR on serial testing. Conclusion: Diagnostic testing combined with incubation period and placental pathology indicate a strong likelihood that intrapartum vertical transmission of SARS-CoV-2 (COVID-19) from mother to baby is possible

The RNA-Binding Protein Musashi1 Affects Medulloblastoma Growth via a Network of Cancer- Related Genes and Is an Indicator of Poor Prognosis

Musashi1 (Msi1) is a highly conserved RNA-binding protein that is required during the development of the nervous system. Msi1 has been characterized as a stem cell marker, controlling the balance between self-renewal and differentiation, and has also been implicated in tumorigenesis, being highly expressed in multiple tumor types. We analyzed Msi1 expression in a large cohort of medulloblastoma samples and found that Msi1 is highly expressed in tumor tissue compared with normal cerebellum. Notably, high Msi1 expression levels proved to be a sign of poor prognosis. Msi1 expression was determined to be particularly high in molecular subgroups 3 and 4 of medulloblastoma. We determined that Msi1 is required for tumorigenesis because inhibition of Msi1 expression by small-interfering RNAs reduced the growth of Daoy medulloblastoma cells in xenografts. To characterize the participation of Msi1 in medulloblastoma, we conducted different high-throughput analyses. Ribonucleoprotein immunoprecipitation followed by microarray analysis (RIP-chip) was used to identify mRNA species preferentially associated with Msi1 protein in Daoy cells. We also used cluster analysis to identify genes with similar or opposite expression patterns to Msi1 in our medulloblastoma cohort. A network study identified RAC1, CTGF, SDCBP, SRC, PRL, and SHC1 as major nodes of an Msi1-associated network. Our results suggest that Msi1 functions as a regulator of multiple processes in medulloblastoma formation and could become an important therapeutic target

Comparative and temporal transcriptome analysis of peste des petits ruminants virus infected goat peripheral blood mononuclear cells

Peste des petits ruminanats virus (PPRV), a morbillivirus causes an acute, highly contagious disease – peste des petits ruminants (PPR), affecting goats and sheep. Sungri/96 vaccine strain is widely used for mass vaccination programs in India against PPR and is considered the most potent vaccine providing long-term immunity. However, occurrence of outbreaks due to emerging PPR viruses may be a challenge. In this study, the temporal dynamics of immune response in goat peripheral blood mononuclear cells (PBMCs) infected with Sungri/96 vaccine virus was investigated by transcriptome analysis. Infected goat PBMCs at 48 h and 120 h post infection revealed 2540 and 2000 differentially expressed genes (DEGs), respectively, on comparison with respective controls. Comparison of the infected samples revealed 1416 DEGs to be altered across time points. Functional analysis of DEGs reflected enrichment of TLR signaling pathways, innate immune response, inflammatory response, positive regulation of signal transduction and cytokine production. The upregulation of innate immune genes during early phase (between 2-5 days) viz. interferon regulatory factors (IRFs), tripartite motifs (TRIM) and several interferon stimulated genes (ISGs) in infected PBMCs and interactome analysis indicated induction of broad-spectrum anti-viral state. Several Transcription factors – IRF3, FOXO3 and SP1 that govern immune regulatory pathways were identified to co-regulate the DEGs. The results from this study, highlighted the involvement of both innate and adaptive immune systems with the enrichment of complement cascade observed at 120 h p.i., suggestive of a link between innate and adaptive immune response. Based on the transcriptome analysis and qRT-PCR validation, an in vitro mechanism for the induction of ISGs by IRFs in an interferon independent manner to trigger a robust immune response was predicted in PPRV infection

Single-cell RNA sequencing uncovers the nuclear decoy lincRNA PIRAT as a regulator of systemic monocyte immunity during COVID-19

The systemic immune response to viral infection is shaped by master transcription fac-tors, such as NF-κB, STAT1, or PU.1. Although long noncoding RNAs (lncRNAs)have been suggested as important regulators of transcription factor activity, their contri-butions to the systemic immunopathologies observed during SARS-CoV-2 infectionhave remained unknown. Here, we employed a targeted single-cell RNA sequencingapproach to reveal lncRNAs differentially expressed in blood leukocytes during severeCOVID-19. Our results uncover the lncRNA PIRAT (PU.1-induced regulator of alar-min transcription) as a major PU.1 feedback-regulator in monocytes, governing the pro-duction of the alarmins S100A8/A9, key drivers of COVID-19 pathogenesis. Knockoutand transgene expression, combined with chromatin-occupancy profiling, characterizedPIRATasanucleardecoyRNA,keepingPU.1frombindingtoalarminpromotersandpromoting its binding to pseudogenes in naïve monocytes. NF-κB–dependent PIRATdown-regulation during COVID-19 consequently releases a transcriptional brake, fuelingalarmin production. Alarmin expression is additionally enhanced by the up-regulation ofthe lncRNA LUCAT1, which promotes NF-κB–dependentgeneexpressionattheexpenseof targets of the JAK-STAT pathway. Our results suggest a major role of nuclear noncod-ing RNA networks in systemic antiviral responses to SARS-CoV-2 in humans

Structural correlations in bacterial metabolic networks

<p>Abstract</p> <p>Background</p> <p>Evolution of metabolism occurs through the acquisition and loss of genes whose products acts as enzymes in metabolic reactions, and from a presumably simple primordial metabolism the organisms living today have evolved complex and highly variable metabolisms. We have studied this phenomenon by comparing the metabolic networks of 134 bacterial species with known phylogenetic relationships, and by studying a neutral model of metabolic network evolution.</p> <p>Results</p> <p>We consider the 'union-network' of 134 bacterial metabolisms, and also the union of two smaller subsets of closely related species. Each reaction-node is tagged with the number of organisms it belongs to, which we denote organism degree (OD), a key concept in our study. Network analysis shows that common reactions are found at the centre of the network and that the average OD decreases as we move to the periphery. Nodes of the same OD are also more likely to be connected to each other compared to a random OD relabelling based on their occurrence in the real data. This trend persists up to a distance of around five reactions. A simple growth model of metabolic networks is used to investigate the biochemical constraints put on metabolic-network evolution. Despite this seemingly drastic simplification, a 'union-network' of a collection of unrelated model networks, free of any selective pressure, still exhibit similar structural features as their bacterial counterpart.</p> <p>Conclusions</p> <p>The OD distribution quantifies topological properties of the evolutionary history of bacterial metabolic networks, and lends additional support to the importance of horizontal gene transfer during bacterial metabolic evolution where new reactions are attached at the periphery of the network. The neutral model of metabolic network growth can reproduce the main features of real networks, but we observe that the real networks contain a smaller common core, while they are more similar at the periphery of the network. This suggests that natural selection and biochemical correlations can act both to diversify and to narrow down metabolic evolution.</p

The DESiGN trial (DEtection of Small for Gestational age Neonate), evaluating the effect of the Growth Assessment Protocol (GAP): study protocol for a randomised controlled trial.

BACKGROUND: Stillbirth rates in the United Kingdom (UK) are amongst the highest of all developed nations. The association between small-for-gestational-age (SGA) foetuses and stillbirth is well established, and observational studies suggest that improved antenatal detection of SGA babies may halve the stillbirth rate. The Growth Assessment Protocol (GAP) describes a complex intervention that includes risk assessment for SGA and screening using customised fundal-height growth charts. Increased detection of SGA from the use of GAP has been implicated in the reduction of stillbirth rates by 22%, in observational studies of UK regions where GAP uptake was high. This study will be the first randomised controlled trial examining the clinical efficacy, health economics and implementation of the GAP programme in the antenatal detection of SGA. METHODS/DESIGN: In this randomised controlled trial, clusters comprising a maternity unit (or National Health Service Trust) were randomised to either implementation of the GAP programme, or standard care. The primary outcome is the rate of antenatal ultrasound detection of SGA in infants found to be SGA at birth by both population and customised standards, as this is recognised as being the group with highest risk for perinatal morbidity and mortality. Secondary outcomes include antenatal detection of SGA by population centiles, antenatal detection of SGA by customised centiles, short-term maternal and neonatal outcomes, resource use and economic consequences, and a process evaluation of GAP implementation. Qualitative interviews will be performed to assess facilitators and barriers to implementation of GAP. DISCUSSION: This study will be the first to provide data and outcomes from a randomised controlled trial investigating the potential difference between the GAP programme compared to standard care for antenatal ultrasound detection of SGA infants. Accurate information on the performance and service provision requirements of the GAP protocol has the potential to inform national policy decisions on methods to reduce the rate of stillbirth. TRIAL REGISTRATION: Primary registry and trial identifying number: ISRCTN 67698474 . Registered on 2 November 2016

Predicting protein linkages in bacteria: Which method is best depends on task

<p>Abstract</p> <p>Background</p> <p>Applications of computational methods for predicting protein functional linkages are increasing. In recent years, several bacteria-specific methods for predicting linkages have been developed. The four major genomic context methods are: Gene cluster, Gene neighbor, Rosetta Stone, and Phylogenetic profiles. These methods have been shown to be powerful tools and this paper provides guidelines for when each method is appropriate by exploring different features of each method and potential improvements offered by their combination. We also review many previous treatments of these prediction methods, use the latest available annotations, and offer a number of new observations.</p> <p>Results</p> <p>Using <it>Escherichia coli </it>K12 and <it>Bacillus subtilis</it>, linkage predictions made by each of these methods were evaluated against three benchmarks: functional categories defined by COG and KEGG, known pathways listed in EcoCyc, and known operons listed in RegulonDB. Each evaluated method had strengths and weaknesses, with no one method dominating all aspects of predictive ability studied. For functional categories, as previous studies have shown, the Rosetta Stone method was individually best at detecting linkages and predicting functions among proteins with shared KEGG categories while the Phylogenetic profile method was best for linkage detection and function prediction among proteins with common COG functions. Differences in performance under COG versus KEGG may be attributable to the presence of paralogs. Better function prediction was observed when using a weighted combination of linkages based on reliability versus using a simple unweighted union of the linkage sets. For pathway reconstruction, 99 complete metabolic pathways in <it>E. coli </it>K12 (out of the 209 known, non-trivial pathways) and 193 pathways with 50% of their proteins were covered by linkages from at least one method. Gene neighbor was most effective individually on pathway reconstruction, with 48 complete pathways reconstructed. For operon prediction, Gene cluster predicted completely 59% of the known operons in <it>E. coli </it>K12 and 88% (333/418)in <it>B. subtilis</it>. Comparing two versions of the <it>E. coli </it>K12 operon database, many of the unannotated predictions in the earlier version were updated to true predictions in the later version. Using only linkages found by both Gene Cluster and Gene Neighbor improved the precision of operon predictions. Additionally, as previous studies have shown, combining features based on intergenic region and protein function improved the specificity of operon prediction.</p> <p>Conclusion</p> <p>A common problem for computational methods is the generation of a large number of false positives that might be caused by an incomplete source of validation. By comparing two versions of a database, we demonstrated the dramatic differences on reported results. We used several benchmarks on which we have shown the comparative effectiveness of each prediction method, as well as provided guidelines as to which method is most appropriate for a given prediction task.</p