111 research outputs found

    Functional Independence and Health-related Functional Status Following Spinal Cord Injury:A Prospective Study of the Association with Physical Capacity

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    Objective: To determine changes in functional independence following spinal cord injury and to evaluate the association between functional independence and physical capacity. Design: Multi-centre prospective cohort study.Subjects: Patients with spinal cord injury admitted for initial rehabilitation.Methods: The motor Functional Independence Measure (FIMmotor) was determined at the start of rehabilitation (n = 176), 3 months later (n = 124), at discharge (n = 160) and one year after discharge from inpatient rehabilitation (n = 133). One year after discharge, physical and social dimensions of health-related functional status (Sickness Impact Profile 68; SIP68) were determined. On each occasion, physical capacity was established by measuring arm muscle strength, peak power output and peak oxygen uptake.Results: Multi-level random coefficient analyses revealed that FIMmotor improved during inpatient rehabilitation, but stabilized thereafter. Changes in FIMmotor were associated with peak power output. Multiple regression models showed that FIMmotor and peak power output at discharge were associated with FIMmotor one year after discharge (R-2 = 0.85), and that peak power output at discharge was associated with the social dimension of the SIP68 (R-2 = 0.18) one year after discharge.Conclusion: Functional independence improves during inpatient rehabilitation, and functional independence is positively associated with peak power output

    Regulatory control and the costs and benefits of biochemical noise

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    Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. How protein concentration fluctuations affect the growth rate of a population of cells, is, however, a wide open question. We present a mathematical model that makes it possible to quantify the effect of protein concentration fluctuations on the growth rate of a population of genetically identical cells. The model predicts that the population's growth rate depends on how the growth rate of a single cell varies with protein concentration, the variance of the protein concentration fluctuations, and the correlation time of these fluctuations. The model also predicts that when the average concentration of a protein is close to the value that maximizes the growth rate, fluctuations in its concentration always reduce the growth rate. However, when the average protein concentration deviates sufficiently from the optimal level, fluctuations can enhance the growth rate of the population, even when the growth rate of a cell depends linearly on the protein concentration. The model also shows that the ensemble or population average of a quantity, such as the average protein expression level or its variance, is in general not equal to its time average as obtained from tracing a single cell and its descendants. We apply our model to perform a cost-benefit analysis of gene regulatory control. Our analysis predicts that the optimal expression level of a gene regulatory protein is determined by the trade-off between the cost of synthesizing the regulatory protein and the benefit of minimizing the fluctuations in the expression of its target gene. We discuss possible experiments that could test our predictions.Comment: Revised manuscript;35 pages, 4 figures, REVTeX4; to appear in PLoS Computational Biolog

    Horizontally acquired glycosyltransferase operons drive salmonellae lipopolysaccharide diversity.

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    The immunodominant lipopolysaccharide is a key antigenic factor for Gram-negative pathogens such as salmonellae where it plays key roles in host adaptation, virulence, immune evasion, and persistence. Variation in the lipopolysaccharide is also the major differentiating factor that is used to classify Salmonella into over 2600 serovars as part of the Kaufmann-White scheme. While lipopolysaccharide diversity is generally associated with sequence variation in the lipopolysaccharide biosynthesis operon, extraneous genetic factors such as those encoded by the glucosyltransferase (gtr) operons provide further structural heterogeneity by adding additional sugars onto the O-antigen component of the lipopolysaccharide. Here we identify and examine the O-antigen modifying glucosyltransferase genes from the genomes of Salmonella enterica and Salmonella bongori serovars. We show that Salmonella generally carries between 1 and 4 gtr operons that we have classified into 10 families on the basis of gtrC sequence with apparent O-antigen modification detected for five of these families. The gtr operons localize to bacteriophage-associated genomic regions and exhibit a dynamic evolutionary history driven by recombination and gene shuffling events leading to new gene combinations. Furthermore, evidence of Dam- and OxyR-dependent phase variation of gtr gene expression was identified within eight gtr families. Thus, as O-antigen modification generates significant intra- and inter-strain phenotypic diversity, gtr-mediated modification is fundamental in assessing Salmonella strain variability. This will inform appropriate vaccine and diagnostic approaches, in addition to contributing to our understanding of host-pathogen interactions

    An Epigenetic Switch Involving Overlapping Fur and DNA Methylation Optimizes Expression of a Type VI Secretion Gene Cluster

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    Type VI secretion systems (T6SS) are macromolecular machines of the cell envelope of Gram-negative bacteria responsible for bacterial killing and/or virulence towards different host cells. Here, we characterized the regulatory mechanism underlying expression of the enteroagregative Escherichia coli sci1 T6SS gene cluster. We identified Fur as the main regulator of the sci1 cluster. A detailed analysis of the promoter region showed the presence of three GATC motifs, which are target of the DNA adenine methylase Dam. Using a combination of reporter fusion, gel shift, and in vivo and in vitro Dam methylation assays, we dissected the regulatory role of Fur and Dam-dependent methylation. We showed that the sci1 gene cluster expression is under the control of an epigenetic switch depending on methylation: fur binding prevents methylation of a GATC motif, whereas methylation at this specific site decreases the affinity of Fur for its binding box. A model is proposed in which the sci1 promoter is regulated by iron availability, adenine methylation, and DNA replication

    Comparative genomics of prevaccination and modern Bordetella pertussis strains

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    Contains fulltext : 89571.pdf (publisher's version ) (Open Access)BACKGROUND: Despite vaccination since the 1950s, pertussis has persisted and resurged. It remains a major cause of infant death worldwide and is the most prevalent vaccine-preventable disease in developed countries. The resurgence of pertussis has been associated with the expansion of Bordetella pertussis strains with a novel allele for the pertussis toxin (Ptx) promoter, ptxP3, which have replaced resident ptxP1 strains. Compared to ptxP1 strains, ptxP3 produce more Ptx resulting in increased virulence and immune suppression. To elucidate how B. pertussis has adapted to vaccination, we compared genome sequences of two ptxP3 strains with four strains isolated before and after the introduction vaccination. RESULTS: The distribution of SNPs in regions involved in transcription and translation suggested that changes in gene regulation play an important role in adaptation. No evidence was found for acquisition of novel genes. Modern strains differed significantly from prevaccination strains, both phylogenetically and with respect to particular alleles. The ptxP3 strains were found to have diverged recently from modern ptxP1 strains. Differences between ptxP3 and modern ptxP1 strains included SNPs in a number of pathogenicity-associated genes. Further, both gene inactivation and reactivation was observed in ptxP3 strains relative to modern ptxP1 strains. CONCLUSIONS: Our work suggests that B. pertussis adapted by successive accumulation of SNPs and by gene (in)activation. In particular changes in gene regulation may have played a role in adaptation

    Origin of the Diversity in DNA Recognition Domains in Phasevarion Associated modA Genes of Pathogenic Neisseria and Haemophilus influenzae

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    Phase variable restriction-modification (R-M) systems have been identified in a range of pathogenic bacteria. In some it has been demonstrated that the random switching of the mod (DNA methyltransferase) gene mediates the coordinated expression of multiple genes and constitutes a phasevarion (phase variable regulon). ModA of Neisseria and Haemophilus influenzae contain a highly variable, DNA recognition domain (DRD) that defines the target sequence that is modified by methylation and is used to define modA alleles. 18 distinct modA alleles have been identified in H. influenzae and the pathogenic Neisseria. To determine the origin of DRD variability, the 18 modA DRDs were used to search the available databases for similar sequences. Significant matches were identified between several modA alleles and mod gene from distinct bacterial species, indicating one source of the DRD variability was via horizontal gene transfer. Comparison of DRD sequences revealed significant mosaicism, indicating exchange between the Neisseria and H. influenzae modA alleles. Regions of high inter- and intra-allele similarity indicate that some modA alleles had undergone recombination more frequently than others, generating further diversity. Furthermore, the DRD from some modA alleles, such as modA12, have been transferred en bloc to replace the DRD from different modA alleles

    The Streptococcus pneumoniae Pilus-1 Displays a Biphasic Expression Pattern

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    The Streptococcus pneumoniae pilus-1 is encoded by pilus islet 1 (PI-1), which has three clonal variants (clade I, II and III) and is present in about 30% of clinical pneumococcal isolates. In vitro and in vivo assays have demonstrated that pilus-1 is involved in attachment to epithelial cells and virulence, as well as protection in mouse models of infection. Several reports suggest that pilus-1 expression is tightly regulated and involves the interplay of numerous genetic regulators, including the PI-1 positive regulator RlrA. In this report we provide evidence that pilus expression, when analyzed at the single-cell level in PI-1 positive strains, is biphasic. In fact, the strains present two phenotypically different sub-populations of bacteria, one that expresses the pilus, while the other does not. The proportions of these two phenotypes are variable among the strains tested and are not influenced by genotype, serotype, growth conditions, colony morphology or by the presence of antibodies directed toward the pilus components. Two sub-populations, enriched in pilus expressing or not expressing bacteria were obtained by means of colony selection and immuno-detection methods for five strains. PI-1 sequencing in the two sub-populations revealed the absence of mutations, thus indicating that the biphasic expression observed is not due to a genetic modification within PI-1. Microarray expression profile and western blot analyses on whole bacterial lysates performed comparing the two enriched sub-populations, revealed that pilus expression is regulated at the transcriptional level (on/off regulation), and that there are no other genes, in addition to those encoded by PI-1, concurrently regulated across the strains tested. Finally, we provide evidence that the over-expression of the RrlA positive regulator is sufficient to induce pilus expression in pilus-1 negative bacteria. Overall, the data presented here suggest that the observed biphasic pilus expression phenotype could be an example of bistability in pneumococcus

    Autoantibody Epitope Spreading in the Pre-Clinical Phase Predicts Progression to Rheumatoid Arthritis

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    Rheumatoid arthritis (RA) is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1–12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-α, IL-6, IL-12p70, and IFN-γ. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis
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