The Mrs1 Splicing Factor Binds the bI3 Group I Intron at Each of Two Tetraloop-Receptor Motifs

Most large ribozymes require protein cofactors in order to function efficiently. The yeast mitochondrial bI3 group I intron requires two proteins for efficient splicing, Mrs1 and the bI3 maturase. Mrs1 has evolved from DNA junction resolvases to function as an RNA cofactor for at least two group I introns; however, the RNA binding site and the mechanism by which Mrs1 facilitates splicing were unknown. Here we use high-throughput RNA structure analysis to show that Mrs1 binds a ubiquitous RNA tertiary structure motif, the GNRA tetraloop-receptor interaction, at two sites in the bI3 RNA. Mrs1 also interacts at similar tetraloop-receptor elements, as well as other structures, in the self-folding Azoarcus group I intron and in the RNase P enzyme. Thus, Mrs1 recognizes general features found in the tetraloop-receptor motif. Identification of the two Mrs1 binding sites now makes it possible to create a model of the complete six-component bI3 ribonucleoprotein. All protein cofactors bind at the periphery of the RNA such that every long-range RNA tertiary interaction is stabilized by protein binding, involving either Mrs1 or the bI3 maturase. This work emphasizes the strong evolutionary pressure to bolster RNA tertiary structure with RNA-binding interactions as seen in the ribosome, spliceosome, and other large RNA machines

ARTEMIS stabilizes the genome and modulates proliferative responses in multipotent mesenchymal cells

<p>Abstract</p> <p>Background</p> <p>Unrepaired DNA double-stranded breaks (DSBs) cause chromosomal rearrangements, loss of genetic information, neoplastic transformation or cell death. The nonhomologous end joining (NHEJ) pathway, catalyzing sequence-independent direct rejoining of DSBs, is a crucial mechanism for repairing both stochastically occurring and developmentally programmed DSBs. In lymphocytes, NHEJ is critical for both development and genome stability. NHEJ defects lead to severe combined immunodeficiency (SCID) and lymphoid cancer predisposition in both mice and humans. While NHEJ has been thoroughly investigated in lymphocytes, the importance of NHEJ in other cell types, especially with regard to tumor suppression, is less well documented. We previously reported evidence that the NHEJ pathway functions to suppress a range of nonlymphoid tumor types, including various classes of sarcomas, by unknown mechanisms.</p> <p>Results</p> <p>Here we investigate roles for the NHEJ factor ARTEMIS in multipotent mesenchymal stem/progenitor cells (MSCs), as putative sarcomagenic cells of origin. We demonstrate a key role for ARTEMIS in sarcoma suppression in a sensitized mouse tumor model. In this context, we found that ARTEMIS deficiency led to chromosomal damage but, paradoxically, enhanced resistance and proliferative potential in primary MSCs subjected to various stresses. Gene expression analysis revealed abnormally regulated stress response, cell proliferation, and signal transduction pathways in ARTEMIS-defective MSCs. Finally, we identified candidate regulatory genes that may, in part, mediate a stress-resistant, hyperproliferative phenotype in preneoplastic ARTEMIS-deficient MSCs.</p> <p>Conclusions</p> <p>Our discoveries suggest that <it>Art </it>prevents genome damage and restrains proliferation in MSCs exposed to various stress stimuli. We propose that deficiency leads to a preneoplastic state in primary MSCs and is associated with aberrant proliferative control and cellular stress resistance. Thus, our data reveal surprising new roles for ARTEMIS and the NHEJ pathway in normal MSC function and fitness relevant to tumor suppression in mesenchymal tissues.</p

Prediction of Disease Severity in Patients with Early Rheumatoid Arthritis by Gene Expression Profiling

In order to test the ability of peripheral blood gene expression profiles to predict future disease severity in patients with early rheumatoid arthritis (RA), a group of 17 patients (1 ± 0.2 years disease duration) was evaluated at baseline for gene expression profiles. Disease status was evaluated after a mean of 5 years using an index combining pain, global and recoded MHAQ scores. Unsupervised and supervised algorithms identified “predictor genes” whose combined expression levels correlated with follow-up disease severity scores. Unsupervised clustering algorithms separated patients into two branches. The only significant difference between these two groups was the disease severity score; demographic variables and medication usage were not different. Supervised T-Test analysis identified 19 “predictor genes” of future disease severity. Results were validated in an independent cohort of subjects of established RA with using Support Vector Machines and K-Nearest-Neighbor Classification. Our study demonstrates that peripheral blood gene expression profiles may be a useful tool to predict future disease severity in patients with early and established RA

Imputation of Ordinal Outcomes: A Comparison of Approaches in Traumatic Brain Injury.

Loss to follow-up and missing outcomes data are important issues for longitudinal observational studies and clinical trials in traumatic brain injury. One popular solution to missing 6-month outcomes has been to use the last observation carried forward (LOCF). The purpose of the current study was to compare the performance of model-based single-imputation methods with that of the LOCF approach. We hypothesized that model-based methods would perform better as they potentially make better use of available outcome data. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study (n = 4509) included longitudinal outcome collection at 2 weeks, 3 months, 6 months, and 12 months post-injury; a total of 8185 Glasgow Outcome Scale extended (GOSe) observations were included in the database. We compared single imputation of 6-month outcomes using LOCF, a multiple imputation (MI) panel imputation, a mixed-effect model, a Gaussian process regression, and a multi-state model. Model performance was assessed via cross-validation on the subset of individuals with a valid GOSe value within 180 ± 14 days post-injury (n = 1083). All models were fit on the entire available data after removing the 180 ± 14 days post-injury observations from the respective test fold. The LOCF method showed lower accuracy (i.e., poorer agreement between imputed and observed values) than model-based methods of imputation, and showed a strong negative bias (i.e., it imputed lower than observed outcomes). Accuracy and bias for the model-based approaches were similar to one another, with the multi-state model having the best overall performance. All methods of imputation showed variation across different outcome categories, with better performance for more frequent outcomes. We conclude that model-based methods of single imputation have substantial performance advantages over LOCF, in addition to providing more complete outcome data

Gradients in the mammalian cerebellar cortex enable Fourier-like transformation and improve storing capacity

Cerebellar granule cells (GCs) make up the majority of all neurons in the vertebrate brain, but heterogeneities among GCs and potential functional consequences are poorly understood. Here, we identified unexpected gradients in the biophysical properties of GCs in mice. GCs closer to the white matter (inner-zone GCs) had higher firing thresholds and could sustain firing with larger current inputs than GCs closer to the Purkinje cell layer (outer-zone GCs). Dynamic Clamp experiments showed that inner- and outer-zone GCs preferentially respond to high- and low-frequency mossy fiber inputs, respectively, enabling dispersion of the mossy fiber input into its frequency components as performed by a Fourier transformation. Furthermore, inner-zone GCs have faster axonal conduction velocity and elicit faster synaptic potentials in Purkinje cells. Neuronal network modeling revealed that these gradients improve spike-timing precision of Purkinje cells and decrease the number of GCs required to learn spike-sequences. Thus, our study uncovers biophysical gradients in the cerebellar cortex enabling a Fourier-like transformation of mossy fiber inputs

Understanding the relationship between cognitive performance and function in daily life after traumatic brain injury

Objective Cognitive impairment is a key cause of disability after traumatic brain injury (TBI) but relationships with overall functioning in daily life are often modest. The aim is to examine cognition at different levels of function and identify domains associated with disability. Methods 1554 patients with mild-to-severe TBI were assessed at 6 months post injury on the Glasgow Outcome Scale-Extended (GOSE), the Short Form-12v2 and a battery of cognitive tests. Outcomes across GOSE categories were compared using analysis of covariance adjusting for age, sex and education. Results Overall effect sizes were small to medium, and greatest for tests involving processing speed (eta(2)(p) 0.057-0.067) and learning and memory (eta(2)(p) 0.048-0.052). Deficits in cognitive performance were particularly evident in patients who were dependent (GOSE 3 or 4) or who were unable to participate in one or more major life activities (GOSE 5). At higher levels of function (GOSE 6-8), cognitive performance was surprisingly similar across categories. There were decreases in performance even in patients reporting complete recovery without significant symptoms. Medium to large effect sizes were present for summary measures of cognition (eta(2)(p) 0.111), mental health (eta(2)(p) 0.131) and physical health (eta(2)(p) 0.252). Conclusions This large-scale study provides novel insights into cognitive performance at different levels of disability and highlights the importance of processing speed in function in daily life. At upper levels of outcome, any influence of cognition on overall function is markedly attenuated and differences in mental health are salient.Peer reviewe

Relationship of admission blood proteomic biomarkers levels to lesion type and lesion burden in traumatic brain injury: a CENTER-TBI study

Background: We aimed to understand the relationship between serum biomarker concentration and lesion type and volume found on computed tomography (CT) following all severities of TBI. Methods: Concentrations of six serum biomarkers (GFAP, NFL, NSE, S100B, t-tau and UCH-L1) were measured in samples obtained <24 hours post-injury from 2869 patients with all severities of TBI, enrolled in the CENTER-TBI prospective cohort study (NCT02210221). Imaging phenotypes were defined as intraparenchymal haemorrhage (IPH), oedema, subdural haematoma (SDH), extradural haematoma (EDH), traumatic subarachnoid haemorrhage (tSAH), diffuse axonal injury (DAI), and intraventricular haemorrhage (IVH). Multivariable polynomial regression was performed to examine the association between biomarker levels and both distinct lesion types and lesion volumes. Hierarchical clustering was used to explore imaging phenotypes; and principal component analysis and k-means clustering of acute biomarker concentrations to explore patterns of biomarker clustering. Findings: 2869 patient were included, 68% (n=1946) male with a median age of 49 years (range 2-96). All severities of TBI (mild, moderate and severe) were included for analysis with majority (n=1946, 68%) having a mild injury (GCS 13-15). Patients with severe diffuse injury (Marshall III/IV) showed significantly higher levels of all measured biomarkers, with the exception of NFL, than patients with focal mass lesions (Marshall grades V/VI). Patients with either DAI+IVH or SDH+IPH+tSAH, had significantly higher biomarker concentrations than patients with EDH. Higher biomarker concentrations were associated with greater volume of IPH (GFAP, S100B, t-tau;adj r2 range:0·48-0·49; p<0·05), oedema (GFAP, NFL, NSE, t-tau, UCH-L1;adj r2 range:0·44-0·44; p<0·01), IVH (S100B;adj r2 range:0.48-0.49; p<0.05), Unsupervised k-means biomarker clustering revealed two clusters explaining 83·9% of variance, with phenotyping characteristics related to clinical injury severity. Interpretation: Interpretation: Biomarker concentration within 24 hours of TBI is primarily related to severity of injury and intracranial disease burden, rather than pathoanatomical type of injury

Relationship of admission blood proteomic biomarkers levels to lesion type and lesion burden in traumatic brain injury: A CENTER-TBI study.

BACKGROUND: We aimed to understand the relationship between serum biomarker concentration and lesion type and volume found on computed tomography (CT) following all severities of TBI. METHODS: Concentrations of six serum biomarkers (GFAP, NFL, NSE, S100B, t-tau and UCH-L1) were measured in samples obtained <24 hours post-injury from 2869 patients with all severities of TBI, enrolled in the CENTER-TBI prospective cohort study (NCT02210221). Imaging phenotypes were defined as intraparenchymal haemorrhage (IPH), oedema, subdural haematoma (SDH), extradural haematoma (EDH), traumatic subarachnoid haemorrhage (tSAH), diffuse axonal injury (DAI), and intraventricular haemorrhage (IVH). Multivariable polynomial regression was performed to examine the association between biomarker levels and both distinct lesion types and lesion volumes. Hierarchical clustering was used to explore imaging phenotypes; and principal component analysis and k-means clustering of acute biomarker concentrations to explore patterns of biomarker clustering. FINDINGS: 2869 patient were included, 68% (n=1946) male with a median age of 49 years (range 2-96). All severities of TBI (mild, moderate and severe) were included for analysis with majority (n=1946, 68%) having a mild injury (GCS 13-15). Patients with severe diffuse injury (Marshall III/IV) showed significantly higher levels of all measured biomarkers, with the exception of NFL, than patients with focal mass lesions (Marshall grades V/VI). Patients with either DAI+IVH or SDH+IPH+tSAH, had significantly higher biomarker concentrations than patients with EDH. Higher biomarker concentrations were associated with greater volume of IPH (GFAP, S100B, t-tau;adj r2 range:0·48-0·49; p<0·05), oedema (GFAP, NFL, NSE, t-tau, UCH-L1;adj r2 range:0·44-0·44; p<0·01), IVH (S100B;adj r2 range:0.48-0.49; p<0.05), Unsupervised k-means biomarker clustering revealed two clusters explaining 83·9% of variance, with phenotyping characteristics related to clinical injury severity. INTERPRETATION: Interpretation: Biomarker concentration within 24 hours of TBI is primarily related to severity of injury and intracranial disease burden, rather than pathoanatomical type of injury. FUNDING: CENTER-TBI is funded by the European Union 7th Framework programme (EC grant 602150)

Relationship of admission blood proteomic biomarkers levels to lesion type and lesion burden in traumatic brain injury: A CENTER-TBI study.

BACKGROUND: We aimed to understand the relationship between serum biomarker concentration and lesion type and volume found on computed tomography (CT) following all severities of TBI. METHODS: Concentrations of six serum biomarkers (GFAP, NFL, NSE, S100B, t-tau and UCH-L1) were measured in samples obtained <24 hours post-injury from 2869 patients with all severities of TBI, enrolled in the CENTER-TBI prospective cohort study (NCT02210221). Imaging phenotypes were defined as intraparenchymal haemorrhage (IPH), oedema, subdural haematoma (SDH), extradural haematoma (EDH), traumatic subarachnoid haemorrhage (tSAH), diffuse axonal injury (DAI), and intraventricular haemorrhage (IVH). Multivariable polynomial regression was performed to examine the association between biomarker levels and both distinct lesion types and lesion volumes. Hierarchical clustering was used to explore imaging phenotypes; and principal component analysis and k-means clustering of acute biomarker concentrations to explore patterns of biomarker clustering. FINDINGS: 2869 patient were included, 68% (n=1946) male with a median age of 49 years (range 2-96). All severities of TBI (mild, moderate and severe) were included for analysis with majority (n=1946, 68%) having a mild injury (GCS 13-15). Patients with severe diffuse injury (Marshall III/IV) showed significantly higher levels of all measured biomarkers, with the exception of NFL, than patients with focal mass lesions (Marshall grades V/VI). Patients with either DAI+IVH or SDH+IPH+tSAH, had significantly higher biomarker concentrations than patients with EDH. Higher biomarker concentrations were associated with greater volume of IPH (GFAP, S100B, t-tau;adj r2 range:0·48-0·49; p<0·05), oedema (GFAP, NFL, NSE, t-tau, UCH-L1;adj r2 range:0·44-0·44; p<0·01), IVH (S100B;adj r2 range:0.48-0.49; p<0.05), Unsupervised k-means biomarker clustering revealed two clusters explaining 83·9% of variance, with phenotyping characteristics related to clinical injury severity. INTERPRETATION: Interpretation: Biomarker concentration within 24 hours of TBI is primarily related to severity of injury and intracranial disease burden, rather than pathoanatomical type of injury. FUNDING: CENTER-TBI is funded by the European Union 7th Framework programme (EC grant 602150)