Structural analysis of two amyloidogenic light chain antibodies, JtoD29A and JtoR68S

Resulting from a high degree of sequence variability, a few human light-chains have a propensity to form amyloid fibrils. The monoclonal V J6 proteins are involved in fibril formation resulting in amyloidosis (AL). A previous study of a· patient (Jto) with multiple myeloma in whom the V J6 protein was deposited in the form of renal tubular casts was shown to form fibrils very slowly. The slow fibril formation resulted from the improved thermodynamic stability gained from an extra salt-bridge between Asp 29 and Arg 66B. To further investigate the effect of this interaction, two mutants Asp 29 to an Ala (JtoD29A) and Arg 66B to a Ser (JtoR68S) that disrupts the salt-bridge were made. Interestingly, the JtoD29A and JtoR68S have very different kinetics of fibril formation. The JtoD29A forms fibrils very slowly, while the JtoR68S forms fibrils at a rate similar to the pathogenic V).6 Wil. In this study we have crystallized JtoD29A and JtoR68S in the same space group P4122 with the same cell dimensions and solved their X-ray structures to 1.6 A and 1.9 A resolution, respectively. Structural comparisons reveal that although there are no significant main-chain conformational changes, there are several side-chain conformational changes due to the mutations. These differences contribute to JtoR68S having a larger exposed hydrophobic solvent surface as compared to JtoD29A. The Arg to Ser mutation in JtoR68S is also responsible for its increased negative electrostatic potential as compared to JtoD29A. We have also attempted to trap a pH induced structural intermediate of JtoR68S. While these findings are preliminary and need to be further investigated, these methods provide new means and insights for studying the amyloid phenomenon

yrGATE: a web-based gene-structure annotation tool for the identification and dissemination of eukaryotic genes

Your Gene structure Annotation Tool for Eukaryotes (yrGATE) provides an Annotation Tool and Community Utilities for worldwide web-based community genome and gene annotation. Annotators can evaluate gene structure evidence derived from multiple sources to create gene structure annotations. Administrators regulate the acceptance of annotations into published gene sets. yrGATE is designed to facilitate rapid and accurate annotation of emerging genomes as well as to confirm, refine, or correct currently published annotations. yrGATE is highly portable and supports different standard input and output formats. The yrGATE software and usage cases are available at

xGDB: open-source computational infrastructure for the integrated evaluation and analysis of genome features

The eXtensible Genome Data Broker (xGDB) provides a software infrastructure consisting of integrated tools for the storage, display, and analysis of genome features in their genomic context. Common features include gene structure annotations, spliced alignments, mapping of repetitive sequence, and microarray probes, but the software supports inclusion of any property that can be associated with a genomic location. The xGDB distribution and user support utilities are available online at the xGDB project website, http://xgdb.sourceforge.net/

ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking

Summary: Unsupervised class discovery is a highly useful technique in cancer research, where intrinsic groups sharing biological characteristics may exist but are unknown. The consensus clustering (CC) method provides quantitative and visual stability evidence for estimating the number of unsupervised classes in a dataset. ConsensusClusterPlus implements the CC method in R and extends it with new functionality and visualizations including item tracking, item-consensus and cluster-consensus plots. These new features provide users with detailed information that enable more specific decisions in unsupervised class discovery

Identification of germline population variants misclassified as cancer-associated somatic variants

IntroductionDatabases used for clinical interpretation in oncology rely on genetic data derived primarily from patients of European ancestry, leading to biases in cancer genetics research and clinical practice. One practical issue that arises in this context is the potential misclassification of multi-ancestral population variants as tumor-associated because they are not represented in reference genomes against which tumor sequencing data is aligned.MethodsTo systematically find misclassified variants, we compared somatic variants in census genes from the Catalogue of Somatic Mutations in Cancer (COSMIC) V99 with multi-ancestral population variants from the Genome Aggregation Databases’ Linkage Disequilibrium (GnomAD). By comparing genomic coordinates, reference, and alternate alleles, we could identify misclassified variants in genes associated with cancer.ResultsWe found 192 of 208 genes in COSMIC’s cancer-associated census genes (92.31%) to be associated with variant misclassifications. Among the 1,906,732 variants in COSMIC, 6,957 variants (0.36%) aligned with normal population variants in GnomAD, concerning for misclassification. The African / African American ancestral population included the greatest number of misclassified variants and also had the greatest number of unique misclassified variants.ConclusionThe direct, systematic comparison of variants from COSMIC for co-occurrence in GnomAD supports a more accurate interpretation of tumor sequencing data and reduces bias related to genomic ancestry

Cafeteria diet-induced obesity causes oxidative damage in white adipose

Obesity continues to be one of the most prominent public health dilemmas in the world. The complex interaction among the varied causes of obesity makes it a particularly challenging problem to address. While typical high-fat purified diets successfully induce weight gain in rodents, we have described a more robust model of diet-induced obesity based on feeding rats a diet consisting of highly palatable, energy-dense human junk foods – the “cafeteria” diet (CAF, 45-53% kcal from fat). We previously reported that CAF-fed rats became hyperphagic, gained more weight, and developed more severe hyperinsulinemia, hyperglycemia, and glucose intolerance compared to the lard-based 45% kcal from fat high fat diet–fed group. In addition, the CAF diet-fed group displayed a higher degree of inflammation in adipose and liver, mitochondrial dysfunction, and an increased concentration of lipid-derived, pro-inflammatory mediators. Building upon our previous findings, we aimed to determine mechanisms that underlie physiologic findings in the CAF diet. We investigated the effect of CAF diet-induced obesity on adipose tissue specifically using expression arrays and immunohistochemistry. Genomic evidence indicated the CAF diet induced alterations in the white adipose gene transcriptome, with notable suppression of glutathione-related genes and pathways involved in mitigating oxidative stress. Immunohistochemical analysis indicated a doubling in adipose lipid peroxidation marker 4-HNE levels compared to rats that remained lean on control standard chow diet. Our data indicates that the CAF diet drives an increase in oxidative damage in white adipose tissue that may affect tissue homeostasis. Oxidative stress drives activation of inflammatory kinases that can perturb insulin signaling leading to glucose intolerance and diabetes

Influence of Differences in Exercise-intensity and Kilograms/Set on Energy Expenditure During and After Maximally Explosive Resistance Exercise

With resistance exercise, greater intensity typically elicits increased energy expenditure, but heavier loads require that the lifter perform more sets of fewer repetitions, which alters the kilograms lifted per set. Thus, the effect of exercise-intensity on energy expenditure has yielded varying results, especially with explosive resistance exercise. This study was designed to examine the effect of exercise-intensity and kilograms/set on energy expenditure during explosive resistance exercise. Ten resistance-trained men (22±3.6 years; 84±6.4 kg, 180±5.1 cm, and 13±3.8 %fat) performed squat and bench press protocols once/week using different exercise-intensities including 48% (LIGHT-48), 60% (MODERATE-60), and 72% of 1-repetition-maximum (1-RM) (HEAVY-72), plus a no-exercise protocol (CONTROL). To examine the effects of kilograms/set, an additional protocol using 72% of 1-RM was performed (HEAVY-72MATCHED) with kilograms/set matched with LIGHT-48 and MODERATE-60. LIGHT-48 was 4 sets of 10 repetitions (4x10); MODERATE-60 4x8; HEAVY-72 5x5; and HEAVY-72MATCHED 4x6.5. Eccentric and concentric repetition speeds, ranges-of-motion, rest-intervals, and total kilograms were identical between protocols. Expired air was collected continuously throughout each protocol using a metabolic cart, [Blood lactate] using a portable analyzer, and bench press peak power were measured. Rates of energy expenditure were significantly greater (p≤0.05) with LIGHT-48 and HEAVY-72MATCHED than HEAVY-72 during squat (7.3±0.7; 6.9±0.6 \u3e 6.1±0.7 kcal/min), bench press (4.8±0.3; 4.7±0.3 \u3e 4.0±0.4 kcal/min), and +5min after (3.7±0.1; 3.7±0.2 \u3e 3.3±0.3 kcal/min), but there were no significant differences in total kcal among protocols. Therefore, exercise-intensity may not effect energy expenditure with explosive contractions, but light loads (~50% of 1-RM) may be preferred because of higher rates of energy expenditure, and since heavier loading requires more sets with lower kilograms/set

BlackOPs: Increasing confidence in variant detection through mappability filtering

Identifying variants using high-throughput sequen-cing data is currently a challenge because true biological variants can be indistinguishable from technical artifacts. One source of technical arti-fact results from incorrectly aligning experimen-tally observed sequences to their true genomic origin (‘mismapping’) and inferring differences in mismapped sequences to be true variants. We de-veloped BlackOPs, an open-source tool that simu-lates experimental RNA-seq and DNA whole exome sequences derived from the reference genome, aligns these sequences by custom parameters, detects variants and outputs a blacklist of positions and alleles caused by mismapping. Blacklist

Energy Content of Seeds of Switchgrass (Panicum virgatum) in the Diet of Mourning Doves (Zenaida macroura) in Southeastern New Mexico

Switchgrass (Panicum virgatum) is a common forage plant that grows over much of the United States. It has drawn interest as a possible feedstock for biofuels, is used as forage for livestock, is planted for soil conservation, and is a component of the diet of some species of wildlife. We analyzed the energy content of seeds of switchgrass obtained from the crops of mourning doves (Zenaida macroura) collected from plains-mesa sand-scrub in Lea and Eddy counties, New Mexico. Seeds were removed from crops and dried for 48 hours at 60°C to remove moisture and standardize masses. Seeds were then analyzed for gross caloric value (i.e., energy content) in an oxygen bomb calorimeter. Energy content of seeds of switchgrass from New Mexico averaged 18.4 J/kg (4.4 kcal/g—standard deviation, 0.7 J/kg [0.2 kcal/g]) and was lower than that of most other food items previously reported from the diet of mourning doves

Development of an Airborne Molecular Direct Detection Doppler Lidar for Tropospheric Wind Profiling

Global measurement of tropospheric winds is a key measurement for understanding atmospheric dynamics and improving numerical weather prediction. Global wind profiles remain a high priority for the operational weather community and also for a variety of research applications including studies of the global hydrologic cycle and transport studies of aerosols and trace species. In addition to space based winds, high altitude airborne Doppler lidar systems flown on research aircraft, UAV's or other advanced sub-orbital platforms would be of great scientific benefit for studying mesoscale dynamics and storm systems such as hurricanes. The Tropospheric Wind Lidar Technology Experiment (TWiLiTE) is a three year program to advance the technology readiness level of the key technologies and subsystems of a molecular direct detection wind lidar system by validating them, at the system level, in an integrated airborne lidar system. The TWiLiTE Doppler lidar system is designed for autonomous operation on the WB57, a high altitude aircraft operated by NASA Johnson. The WE357 is capable of flying well above the midlatitude tropopause so the downward looking lidar will measure complete profiles of the horizontal wind field through the lower stratosphere and the entire troposphere. The completed system will have the capability to profile winds in clear air from the aircraft altitude of 18 km to the surface with 250 m vertical resolution and < 3 mis velocity accuracy. Progress in technology development and status of the instrument design will be presented