Neural Mechanisms Underlying Breathing Complexity

Breathing is maintained and controlled by a network of automatic neurons in the brainstem that generate respiratory rhythm and receive regulatory inputs. Breathing complexity therefore arises from respiratory central pattern generators modulated by peripheral and supra-spinal inputs. Very little is known on the brainstem neural substrates underlying breathing complexity in humans. We used both experimental and theoretical approaches to decipher these mechanisms in healthy humans and patients with chronic obstructive pulmonary disease (COPD). COPD is the most frequent chronic lung disease in the general population mainly due to tobacco smoke. In patients, airflow obstruction associated with hyperinflation and respiratory muscles weakness are key factors contributing to load-capacity imbalance and hence increased respiratory drive. Unexpectedly, we found that the patients breathed with a higher level of complexity during inspiration and expiration than controls. Using functional magnetic resonance imaging (fMRI), we scanned the brain of the participants to analyze the activity of two small regions involved in respiratory rhythmogenesis, the rostral ventro-lateral (VL) medulla (pre-Bötzinger complex) and the caudal VL pons (parafacial group). fMRI revealed in controls higher activity of the VL medulla suggesting active inspiration, while in patients higher activity of the VL pons suggesting active expiration. COPD patients reactivate the parafacial to sustain ventilation. These findings may be involved in the onset of respiratory failure when the neural network becomes overwhelmed by respiratory overload We show that central neural activity correlates with airflow complexity in healthy subjects and COPD patients, at rest and during inspiratory loading. We finally used a theoretical approach of respiratory rhythmogenesis that reproduces the kernel activity of neurons involved in the automatic breathing. The model reveals how a chaotic activity in neurons can contribute to chaos in airflow and reproduces key experimental fMRI findings.     

First Evidence of Simultaneous Circulation of Three Different Dengue Virus Serotypes in Africa

Gabon, in Central Africa, was affected for the first time in 2007 and then in 2010 by simultaneous outbreaks of chikungunya and Dengue serotype 2 (DENV-2) viruses. Through the national surveillance of dengue-like syndromes between 2007 and 2010, we observed continuous circulation of DENV-2 in a southward movement. This rapid spread of DENV-2 was associated with the emergence of DENV-1 in 2007 and DENV-3 in 2010. Interestingly, we detected six DENV-2 infected patients with hemorrhagic signs during the second outbreak in 2010. Although these cases do not meet all standard WHO criteria for severe Dengue with hemorrhage (formerly DHF), this is the first report of several dengue fever cases associated with hemorrhagic signs during a simultaneous circulation of different DENV serotypes in Africa. Together, these findings suggest that DENV is becoming more widely established on this continent and that DHF will likely become a serious public-health problem in the near future.     

Combination of a Proteomics Approach and Reengineering of Meso Scale Network Models for Prediction of Mode-of-Action for Tyrosine Kinase Inhibitors

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs.     

The Signal Sequence Influences Post-Translational ER Translocation at Distinct Stages

The metazoan Sec61 translocon transports polypeptides into and across the membrane of the endoplasmic reticulum via two major routes, a well-established co-translational pathway and a post-translational alternative. We have used two model substrates to explore the elements of a secretory protein precursor that preferentially direct it towards a co- or post-translational pathway for ER translocation. Having first determined the capacity of precursors to enter ER derived microsomes post-translationally, we then exploited semi-permeabilized mammalian cells specifically depleted of key membrane components using siRNA to address their contribution to the membrane translocation process. These studies suggest precursor chain length is a key factor in the post-translational translocation at the mammalian ER, and identify Sec62 and Sec63 as important components acting on this route. This role for Sec62 and Sec63 is independent of the signal sequence that delivers the precursor to the ER. However, the signal sequence can influence the subsequent membrane translocation process, conferring sensitivity to a small molecule inhibitor and dictating reliance on the molecular chaperone BiP. Our data support a model where secretory protein precursors that fail to engage the signal recognition particle, for example because they are short, are delivered to the ER membrane via a distinct route that is dependent upon both Sec62 and Sec63. Although this requirement for Sec62 and Sec63 is unaffected by the specific signal sequence that delivers a precursor to the ER, this region can influence subsequent events, including both Sec61 mediated transport and the importance of BiP for membrane translocation. Taken together, our data suggest that an ER signal sequence can regulate specific aspects of Sec61 mediated membrane translocation at a stage following Sec62/Sec63 dependent ER delivery.     

Influence of Vectors’ Risk-Spreading Strategies and Environmental Stochasticity on the Epidemiology and Evolution of Vector-Borne Diseases: The Example of Chagas’ Disease

Insects are known to display strategies that spread the risk of encountering unfavorable conditions, thereby decreasing the extinction probability of genetic lineages in unpredictable environments. To what extent these strategies influence the epidemiology and evolution of vector-borne diseases in stochastic environments is largely unknown. In triatomines, the vectors of the parasite Trypanosoma cruzi, the etiological agent of Chagas’ disease, juvenile development time varies between individuals and such variation most likely decreases the extinction risk of vector populations in stochastic environments. We developed a simplified multi-stage vector-borne SI epidemiological model to investigate how vector risk-spreading strategies and environmental stochasticity influence the prevalence and evolution of a parasite. This model is based on available knowledge on triatomine biodemography, but its conceptual outcomes apply, to a certain extent, to other vector-borne diseases. Model comparisons between deterministic and stochastic settings led to the conclusion that environmental stochasticity, vector risk-spreading strategies (in particular an increase in the length and variability of development time) and their interaction have drastic consequences on vector population dynamics, disease prevalence, and the relative short-term evolution of parasite virulence. Our work shows that stochastic environments and associated risk-spreading strategies can increase the prevalence of vector-borne diseases and favor the invasion of more virulent parasite strains on relatively short evolutionary timescales. This study raises new questions and challenges in a context of increasingly unpredictable environmental variations as a result of global climate change and human interventions such as habitat destruction or vector control.     

Sedentary Time and Markers of Chronic Low-Grade Inflammation in a High Risk Population

Background

Sedentary behaviour has been identified as a distinct risk factor for several health outcomes. Nevertheless, little research has been conducted into the underlying mechanisms driving these observations. This study aimed to investigate the association of objectively measured sedentary time and breaks in sedentary time with markers of chronic low-grade inflammation and adiposity in a population at a high risk of type 2 diabetes mellitus.

Methods

This study reports data from an ongoing diabetes prevention programme conducted in Leicestershire, UK. High risk individuals were recruited from 10 primary care practices. Sedentary time (<25counts per 15s) was measured using Actigraph GT3X accelerometers (15s epochs). A break was considered as any interruption in sedentary time (≥25counts per 15s). Biochemical outcomes included interleukin-6 (IL-6), C-reactive protein (CRP), leptin, adiponectin and leptin:adiponectin ratio (LAR). A sensitivity analysis investigated whether results were affected by removing participants with a CRP level >10 mg/L, as this can be indicative of acute inflammation.

Results

558 participants (age = 63.6±7.7years; male = 64.7%) had complete adipokine and accelerometer data. Following adjustment for various confounders, sedentary time was detrimentally associated with CRP (β = 0.176±0.057, p = 0.002), IL-6 (β = 0.242±0.056, p = <0.001), leptin (β = 0.146±0.043, p = <0.001) and LAR (β = 0.208±0.052, p = <0.001). Associations were attenuated after further adjustment for moderate-to-vigorous physical activity (MVPA) with only IL-6 (β = 0.231±0.073, p = 0.002) remaining significant; this result was unaffected after further adjustment for body mass index and glycosylated haemoglobin (HbA_1c). Similarly, breaks in sedentary time were significantly inversely associated with IL-6 (β = −0.094±0.047, p = 0.045) and leptin (β = −0.075±0.037, p = 0.039); however, these associations were attenuated after adjustment for accelerometer derived variables. Excluding individuals with a CRP level >10 mg/L consistently attenuated the significant associations across all markers of inflammation.

Conclusion

These novel findings from a high risk population recruited through primary care suggest that sedentary behaviour may influence markers associated with inflammation, independent of MVPA, glycaemia and adiposity.     

The Homeobox Gene MEIS1 Is Methylated in BRAF p.V600E Mutated Colon Tumors

Development of colorectal cancer (CRC) can occur both via gene mutations in tumor suppressor genes and oncogenes, as well as via epigenetic changes, including DNA methylation. Site-specific methylation in CRC regulates expression of tumor-associated genes. Right-sided colon tumors more frequently have BRAF ^p.V600E mutations and have higher methylation grades when compared to left-sided malignancies. The aim of this study was to identify DNA methylation changes associated with BRAF ^p.V600E mutation status. We performed methylation profiling of colon tumor DNA, isolated from frozen sections enriched for epithelial cells by macro-dissection, and from paired healthy tissue. Single gene analyses comparing BRAF ^p.V600E with BRAF wild type revealed MEIS1 as the most significant differentially methylated gene (log₂ fold change: 0.89, false discovery rate-adjusted P-value 2.8*10^-9). This finding was validated by methylation-specific PCR that was concordant with the microarray data. Additionally, validation in an independent cohort (n=228) showed a significant association between BRAF ^p.V600E and MEIS1 methylation (OR: 13.0, 95% CI: 5.2 - 33.0, P<0.0001). MEIS1 methylation was associated with decreased MEIS1 gene expression in both patient samples and CRC cell lines. The same was true for gene expression of a truncated form of MEIS1, MEIS1 _D27, which misses exon 8 and has a proposed tumor suppression function. To trace the origin of MEIS1 promoter methylation, 14 colorectal tumors were flow-sorted. Four out of eight BRAF ^p.V600E tumor epithelial fractions (50%) showed MEIS1 promoter methylation, as well as three out of eight BRAF ^p.V600E stromal fractions (38%). Only one out of six BRAF wild type showed MEIS1 promoter methylation in both the epithelial tumor and stromal fractions (17%). In conclusion, BRAF ^p.V600E colon tumors showed significant MEIS1 promoter methylation, which was associated with decreased MEIS1 gene expression.     

Within-laboratory and between-laboratory variability in the measurement of anti-müllerian hormone determined within an external quality assurance scheme

Ten laboratories in an external quality assurance scheme used the same assay to measure anti-müllerian hormone concentration (Beckman Coulter Gen II) and received twenty serum samples distributed over a 15 month period. The mean bias for all results was only ?0.089%, but there was large coefficient of repeatability of 38.8% (sample bias ranged from ?37.9% to +54.7%). While each laboratory showed good reproducibility, there was a wide range of average values relative to the consensus value from ?24.0% to +22.7%. This between-laboratory variability suggests clinicians should use the same laboratory to avoid problems with result interpretation.     

Genetic Association Analyses of Nitric Oxide Synthase Genes and Neural Tube Defects Vary by Phenotype

Neural tube defects (NTDs) are caused by improper neural tube closure during the early stages of embryonic development. NTDs are hypothesized to have a complex genetic origin and numerous candidate genes have been proposed. The nitric oxide synthase 3 (NOS3) G594T polymorphism has been implicated in risk for spina bifida, and interactions between that single nucleotide polymorphism (SNP) and the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism have also been observed. To evaluate other genetic variation in the NO pathway in the development of NTDs, we examined all three NOS genes: NOS1, NOS2, and NOS3. Using 3109 Caucasian samples in 745 families, we evaluated association in the overall dataset and within specific phenotypic subsets. Haplotype tagging SNPs in the NOS genes were tested for genetic association with NTD subtypes, both for main effects as well as for the presence of interactions with the MTHFR C677T polymorphism. Nominal main effect associations were found with all subtypes, across all three NOS genes, and interactions were observed between SNPs in all three NOS genes and MTHFR C677T. Unlike the previous report, the most significant associations in our dataset were with cranial subtypes and the AG genotype of rs4795067 in NOS2 (p = 0.0014) and the interaction between the rs9658490 G allele in NOS1 and MTHFR 677TT genotype (p = 0.0014). Our data extend the previous findings by implicating a role for all three NOS genes, independently and through interactions with MTHFR, in risk not only for spina bifida, but all NTD subtypes.