Prevalence of Coxiella burnetii seropositivity and shedding in farm, pet and feral cats and associated risk factors in farm cats in Quebec, Canada.

Cats represent a potential source of Coxiella burnetii, the aetiological agent of Q fever in humans. The prevalence and risk factors of C. burnetii infection in farm, pet and feral cats were studied in Quebec, Canada, using a cross-sectional study. Serum samples were tested using a specific enzyme-linked immunosorbent assay (ELISA) for the presence of antibodies against C. burnetii, whereas rectal swabs were assayed using real-time quantitative polymerase chain reaction (qPCR) for the molecular detection of the bacteria. Potential risk factors for farm cats were investigated using clinical examinations, questionnaires and results from a concurrent study on C. burnetii farm status. A total of 184 cats were tested: 59 from ruminant farms, 73 pets and 52 feral cats. Among farm cats, 2/59 (3.4%) were ELISA-positive, 3/59 (5.1%) were ELISA-doubtful and 1/59 (1.7%) was qPCR-positive. All pets and feral cats were negative to C. burnetii ELISA and qPCR. Farm cat positivity was associated with a positive C. burnetii status on the ruminant farm (prevalence ratio = 7.6, P = 0.03). Our results suggest that although pet and feral cats do not seem to pose a great C. burnetii risk to public health, more active care should be taken when in contact with cats from ruminant farms.

Established and emerging strategies to crack the genetic code of obesity.

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.

Revisiting the evolutionary origins of obesity: lazy versus peppy-thrifty genotype hypothesis.

The recent global obesity epidemic is attributed to major societal and environmental changes, such as excessive energy intake and sedentary lifestyle. However, exposure to 'obesogenic' environments does not necessarily result in obesity at the individual level, as 40-75% of body mass index variation in population is attributed to genetic differences. The thrifty genotype theory posits that genetic variants promoting efficient food sequestering and optimal deposition of fat during periods of food abundance were evolutionarily advantageous for the early hunter-gatherer and were positively selected. However, the thrifty genotype is likely too simplistic and fails to provide a justification for the complex distribution of obesity predisposing gene variants and for the broad range of body mass index observed in diverse ethnic groups. This review proposes that gene pleiotropy may better account for the variability in the distribution of obesity susceptibility alleles across modern populations. We outline the lazy-thrifty versus peppy-thrifty genotype hypothesis and detail the body of evidence in the literature in support of this novel concept. Future population genetics and mathematical modelling studies that account for pleiotropy may further improve our understanding of the evolutionary origins of the current obesity epidemic.

Obesity genetics: insights from the Pakistani population.

The Pakistani population is extensively diverse, indicating a genetic admixture of European and Central/West Asian migrants with indigenous South Asian gene pools. Pakistanis are organized in different ethnicities/castes based on cultural, linguistic and geographical origin. While Pakistan is facing a rapid nutritional transition, the rising prevalence of obesity is driving a growing burden of health complications and mortality. This represents a unique opportunity for the research community to study the interplay between obesogenic environmental changes and obesity predisposing genes in the time frame of one generation. This review recapitulates the ancestral origins of Pakistani population, the societal determinants of the rise in obesity and its governmental management. We describe the contribution of syndromic, monogenic non-syndromic and polygenic obesity genes identified in the Pakistani population. We then discuss the utility of gene identification approaches based on large consanguineous families and original gene × environment interaction study designs in discovering new obesity genes and causal pathways. Elucidation of the genetic basis of obesity in the Pakistani population may result in improved methods of obesity prevention and treatment globally.

On the origin of obesity: identifying the biological, environmental and cultural drivers of genetic risk among human populations.

Genetic predisposition to obesity presents a paradox: how do genetic variants with a detrimental impact on human health persist through evolutionary time? Numerous hypotheses, such as the thrifty genotype hypothesis, attempt to explain this phenomenon yet fail to provide a justification for the modern obesity epidemic. In this critical review, we appraise existing theories explaining the evolutionary origins of obesity and explore novel biological and sociocultural agents of evolutionary change to help explain the modern-day distribution of obesity-predisposing variants. Genetic drift, acting as a form of 'blind justice,' may randomly affect allele frequencies across generations while gene pleiotropy and adaptations to diverse environments may explain the rise and subsequent selection of obesity risk alleles. As an adaptive response, epigenetic regulation of gene expression may impact the manifestation of genetic predisposition to obesity. Finally, exposure to malnutrition and disease epidemics in the wake of oppressive social systems, culturally mediated notions of attractiveness and desirability, and diverse mating systems may play a role in shaping the human genome. As an important first step towards the identification of important drivers of obesity gene evolution, this review may inform empirical research focused on testing evolutionary theories by way of population genetics and mathematical modelling.

Hermitian splines for modeling biological soft tissue systems that exhibit nonlinear force-elongation curves.

Numerical simulation of soft tissue mechanical properties is a critical step in developing valuable biomechanical models of live organisms. A cubic Hermitian spline optimization routine is proposed in this paper to model nonlinear experimental force-elongation curves of soft tissues, in particular when modeled as lumped elements. Boundary conditions are introduced to account for the positive definiteness and the particular curvature of the experimental curve to be fitted. The constrained least-square routine minimizes user intervention and optimizes fitting of the experimental data across the whole fitting range. The routine provides coefficients of a Hermitian spline or corresponding knots that are compatible with a number of constraints that are suitable for modeling soft tissue tensile curves. These coefficients or knots may become inputs to user-defined component properties of various modeling software. Splines are particularly advantageous over the well-known exponential model to account for the traction curve flatness at low elongations and to allow for more flexibility in the fitting process. This is desirable as soft tissue models begin to include more complex physical phenomena.

Variation in mitochondrial function in hypoxia-sensitive and hypoxia-tolerant human glioma cells.

We have shown previously that human glioblastoma multiforme cells vary in their ability to survive under hypoxic conditions. Under oxygen limiting conditions, hypoxia-tolerant cells decrease their oxygen consumption rate whereas hypoxia-sensitive cells continue to consume oxygen at a relatively steady rate until the oxygen supply becomes exhausted. We now show that hypoxia-tolerant and hypoxia-sensitive cells exhibit distinct patterns of mitochondrial function in response to hypoxic challenge. Hypoxia-tolerant cell lines retain stable mitochondrial membrane potential and ATP concentration when incubated under oxygen limiting conditions. In addition, hypoxia-tolerant cell lines are consistently more sensitive to a wide spectrum of inhibitors of mitochondrial function than are hypoxia-sensitive cells. In contrast, the hypoxia-sensitive cells are unable to maintain stable mitochondrial membrane potential and ATP levels when incubated at reduced oxygen tension. These results demonstrate significant differences in the mitochondrial function between these two phenotypes and reinforce previous data that suggest a regulatory role for mitochondria in the development of hypoxia tolerance.

Automated discovery of structural signatures of protein fold and function.

There are constraints on a protein sequence/structure for it to adopt a particular fold. These constraints could be either a local signature involving particular sequences or arrangements of secondary structure or a global signature involving features along the entire chain. To search systematically for protein fold signatures, we have explored the use of Inductive Logic Programming (ILP). ILP is a machine learning technique which derives rules from observation and encoded principles. The derived rules are readily interpreted in terms of concepts used by experts. For 20 populated folds in SCOP, 59 rules were found automatically. The accuracy of these rules, which is defined as the number of true positive plus true negative over the total number of examples, is 74% (cross-validated value). Further analysis was carried out for 23 signatures covering 30% or more positive examples of a particular fold. The work showed that signatures of protein folds exist, about half of rules discovered automatically coincide with the level of fold in the SCOP classification. Other signatures correspond to homologous family and may be the consequence of a functional requirement. Examination of the rules shows that many correspond to established principles published in specific literature. However, in general, the list of signatures is not part of standard biological databases of protein patterns. We find that the length of the loops makes an important contribution to the signatures, suggesting that this is an important determinant of the identity of protein folds. With the expansion in the number of determined protein structures, stimulated by structural genomics initiatives, there will be an increased need for automated methods to extract principles of protein folding from coordinates.

Generating protein three-dimensional fold signatures using inductive logic programming.

Inductive logic programming (ILP) has been applied to automatically discover protein fold signatures. This paper investigates the use of topological information to circumvent problems encountered during previous experiments, namely (1) matching of non-structurally related secondary structures and (2) scaling problems. Cross-validation tests were carried out for 20 folds. The overall estimated accuracy is 73.37+/-0.35%. The new representation allows us to process the complete set of examples, while previously it was necessary to sample the negative examples. Topological information is used in approximately 90% of the rules presented here. Information about the topology of a sheet is present in 63% of the rules. This set of rules presents characteristics of the overall architecture of the fold. In contrast, 26% of the rules contain topological information which is limited to the packing of a restricted number of secondary structures, as such, the later set resembles those found in our previous studies.

Tn5-induced lipopolysaccharide mutations in Bordetella pertussis that affect outer membrane function.

An LPSB-specific mAb was used to screen for ten Tn5 insertion mutants of Bordetella pertussis which have LPS which is phenotypically distinct from either wild-type LPSAB or LPSB. Silver-strained SDS-PAGE gels showed nine different LPS phenotypes, six of which contain two clinically undocumented LPS bands, designated IntA and IntB based on their proximity to the LPSA and LPSB bands, respectively. Binding assays with LPSA- and LPSB-specific mAbs established changes in epitope exposure for the various mutant LPS, both in cell-free form and as presented on the surface of whole cells. The possible involvement of a number of genes, both structural and regulatory, was indicated in production of the altered phenotypes. PFGE and Southern blotting showed that the Tn5 inserts of seven mutants mapped to a region of the B. pertussis chromosome shown previously to encode the bpl gene products of LPS biosynthesis. Mutants MLT3, MLT5 and MLT8, however, mapped to distinctly different parts of the chromosome. In addition, mutants MLT2 and MLT3 contributed to an accelerated frequency in the appearance of avirulent phase organisms despite their Tn5 inserts being over 1000 bp from the bvglASR locus. The alterations in LPS structure in the mutants changed their reactivity to strain-specific mAbs and their sensitivity to hydrophobic and hydrophilic antibiotics.

A predicted consensus structure for the N-terminal fragment of the heat shock protein HSP90 family.

A secondary structure has been predicted for the heat shock protein HSP90 family from an aligned set of homologous protein sequences by using a transparent method in both manual and automated implementation that extracts conformational information from patterns of variation and conservation within the family. No statistically significant sequence similarity relates this family to any protein with known crystal structure. However, the secondary structure prediction, together with the assignment of active site positions and possible biochemical properties, suggest that the fold is similar to that seen in N-terminal domain of DNA gyrase B (the ATPase fragment).

The combination of symbolic and numerical computation for three-dimensional modeling of RNA.

Three-dimensional (3-D) structural models of RNA are essential for understanding of the cellular roles played by RNA. Such models have been obtained by a technique based on a constraint satisfaction algorithm that allows for the facile incorporation of secondary and other structural information. The program generates 3-D structures of RNA with atomic-level resolution that can be refined by numerical techniques such as energy minimization. The precision of this technique was evaluated by comparing predicted transfer RNA loop and RNA pseudoknot structures with known or consensus structures. The root-mean-square deviation (2.0 to 3.0 angstroms before minimization) between predicted and control structures reveal this system to be an effective method in modeling RNA.

Similarities of the cataleptic state induced by beta-endorphin and morphine.

A variety of behavioral tests were used to characterize the cataleptic state induced by various treatments. Besides catalepsy, posture, locomotion, rigidity and the presence of reflexive responses were assessed. Measures of analgesia and body temperature were taken. The behavioral profiles of beta-endorphin, morphine, etonitazene, haloperidol, arecoline and GABA were compared at the time maximal catalepsy scores were obtained. Results indicated that, for an equivalent degree of catalepsy, the profile of beta-endorphin was similar to that of opiates, except for changes in body temperature; beta-endorphin's profile differed markedly from that of haloperidol, arecoline and GABA. Catalepsy was less pronounced with the latter two drugs. There were similarities in the behavioral profile of haloperidol and arecoline.