Non-Conjugated Small Molecule FRET for Differentiating Monomers from Higher Molecular Weight Amyloid Beta Species

Background: Systematic differentiation of amyloid (Aβ) species could be important for diagnosis of Alzheimer's disease (AD). In spite of significant progress, controversies remain regarding which species are the primary contributors to the AD pathology, and which species could be used as the best biomarkers for its diagnosis. These controversies are partially caused by the lack of reliable methods to differentiate the complicated subtypes of Aβ species. Particularly, differentiation of Aβ monomers from toxic higher molecular weight species (HrMW) would be beneficial for drug screening, diagnosis, and molecular mechanism studies. However, fast and cheap methods for these specific aims are still lacking. Principal Findings: We demonstrated the feasibility of a non-conjugated FRET (Förster resonance energy transfer) technique that utilized amyloid beta (Aβ) species as intrinsic platforms for the FRET pair assembly. Mixing two structurally similar curcumin derivatives that served as the small molecule FRET pair with Aβ40 aggregates resulted in a FRET signal, while no signal was detected when using Aβ40 monomer solution. Lastly, this FRET technique enabled us to quantify the concentrations of Aβ monomers and high molecular weight species in solution. Significance: We believe that this FRET technique could potentially be used as a tool for screening for inhibitors of Aβ aggregation. We also suggest that this concept could be generalized to other misfolded proteins/peptides implicated in various pathologies including amyloid in diabetes, prion in bovine spongiform encephalopathy, tau protein in AD, and α-synuclein in Parkinson disease.National Institute on Aging (K25AG036760

3D Profile-Based Approach to Proteome-Wide Discovery of Novel Human Chemokines

Chemokines are small secreted proteins with important roles in immune responses. They consist of a conserved three-dimensional (3D) structure, so-called IL8-like chemokine fold, which is supported by disulfide bridges characteristic of this protein family. Sequence- and profile-based computational methods have been proficient in discovering novel chemokines by making use of their sequence-conserved cysteine patterns. However, it has been recently shown that some chemokines escaped annotation by these methods due to low sequence similarity to known chemokines and to different arrangement of cysteines in sequence and in 3D. Innovative methods overcoming the limitations of current techniques may allow the discovery of new remote homologs in the still functionally uncharacterized fraction of the human genome. We report a novel computational approach for proteome-wide identification of remote homologs of the chemokine family that uses fold recognition techniques in combination with a scaffold-based automatic mapping of disulfide bonds to define a 3D profile of the chemokine protein family. By applying our methodology to all currently uncharacterized human protein sequences, we have discovered two novel proteins that, without having significant sequence similarity to known chemokines or characteristic cysteine patterns, show strong structural resemblance to known anti-HIV chemokines. Detailed computational analysis and experimental structural investigations based on mass spectrometry and circular dichroism support our structural predictions and highlight several other chemokine-like features. The results obtained support their functional annotation as putative novel chemokines and encourage further experimental characterization. The identification of remote homologs of human chemokines may provide new insights into the molecular mechanisms causing pathologies such as cancer or AIDS, and may contribute to the development of novel treatments. Besides, the genome-wide applicability of our methodology based on 3D protein family profiles may open up new possibilities for improving and accelerating protein function annotation processes

Development of an educational intervention for patients with Irritable Bowel Syndrome (IBS) – a pilot study

<p>Abstract</p> <p>Background</p> <p>Many IBS patients experience that they receive limited information and that the health care system does not take their complaints seriously. We aimed to develop a structured patient education, an 'IBS school', and investigate if the efficacy could be evaluated in terms of improved knowledge, symptom severity and health related quality of life (HRQOL).</p> <p>Methods</p> <p>The IBS school consisted of six weekly two hour sessions in a group setting. Five different health care professionals were responsible for one session each. Questionnaires covering patients' experience of the education, perceived knowledge about IBS, gastrointestinal symptoms, and HRQOL, were used for evaluation at baseline and at three, six, and twelve months after education.</p> <p>Results</p> <p>Twelve IBS patients were included. The patients were overall satisfied with the IBS school. In line with this, the gastrointestinal symptoms, HRQOL, and perceived knowledge about IBS improved significantly after the education.</p> <p>Conclusion</p> <p>An IBS school seems to be a proper method to meet the patients' need of information about IBS and also to improve the patients' gastrointestinal symptoms, HRQOL, and knowledge about IBS. Further controlled studies are now needed in larger numbers of patients to confirm these preliminary results in order to implement this intervention in clinical practice.</p

Deep Sequencing of the Oral Microbiome Reveals Signatures of Periodontal Disease

The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (∼2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ∼90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Status and determinants of intra-household food allocation in rural Nepal.

BACKGROUND/OBJECTIVES: Understanding of the patterns and predictors of intra-household food allocation could enable nutrition programmes to better target nutritionally vulnerable individuals. This study aims to characterise the status and determinants of intra-household food and nutrient allocation in Nepal. SUBJECTS/METHODS: Pregnant women, their mothers-in-law and male household heads from Dhanusha and Mahottari districts in Nepal responded to 24-h dietary recalls, thrice repeated on non-consecutive days (n = 150 households; 1278 individual recalls). Intra-household inequity was measured using ratios between household members in food intakes (food shares); food-energy intake proportions ('food shares-to-energy shares', FS:ES); calorie-requirement proportions ('relative dietary energy adequacy ratios', RDEARs) and mean probability of adequacy for 11 micronutrients (MPA ratios). Hypothesised determinants were collected during the recalls, and their associations with the outcomes were tested using multivariable mixed-effects linear regression models. RESULTS: Women's diets (pregnant women and mothers-in-law) consisted of larger FS:ES of starchy foods, pulses, fruits and vegetables than male household heads, whereas men had larger FS:ES of animal-source foods. Pregnant women had the lowest MPA (37%) followed by their mothers-in-law (52%), and male household heads (57%). RDEARs between pregnant women and household heads were 31% higher (log-RDEAR coeff=0.27 (95% CI 0.12, 0.42), P < 0.001) when pregnant women earned more or the same as their spouse, and log-MPA ratios between pregnant women and mothers-in-law were positively associated with household-level calorie intakes (coeff=0.43 (0.23, 0.63), P < 0.001, per 1000 kcal). CONCLUSIONS: Pregnant women receive inequitably lower shares of food and nutrients, but this could be improved by increasing pregnant women's cash earnings and household food security

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries