A systematic proteomic study of seed filling in soybean. Establishment of high-resolution two-dimensional reference maps, expression profiles, and an interactive proteome database

A high-throughput proteomic approach was employed to determine the expression profile and identity of hundreds of proteins during seed filling in soybean (Glycine max) cv Maverick. Soybean seed proteins were analyzed at 2, 3, 4, 5, and 6 weeks after flowering using two-dimensional gel electrophoresis and matrix-assisted laser desorption ionization time-of-flight mass spectrometry. This led to the establishment of high-resolution proteome reference maps, expression profiles of 679 spots, and corresponding matrix-assisted laser desorption ionization time-of-flight mass spectrometry spectra for each spot. Database searching with these spectra resulted in the identification of 422 proteins representing 216 nonredundant proteins. These proteins were classified into 14 major functional categories. Proteins involved in metabolism, protein destination and storage, metabolite transport, and disease/defense were the most abundant. For each functional category, a composite expression profile is presented to gain insight into legume seed physiology and the general regulation of proteins associated with each functional class. Using this approach, an overall decrease in metabolism-related proteins versus an increase in proteins associated with destination and storage was observed during seed filling. The accumulation of unknown proteins, sucrose transport and cleavage enzymes, cysteine and methionine biosynthesis enzymes, 14-3-3-like proteins, lipoxygenases, storage proteins, and allergenic proteins during seed filling is also discussed. A user-intuitive database (http://oilseedproteomics.missouri.edu) was developed to access these data for soybean and other oilseeds currently being investigated.     

EVA-1 Functions as an UNC-40 Co-receptor to Enhance Attraction to the MADD-4 Guidance Cue in Caenorhabditis elegans

We recently discovered a secreted and diffusible midline cue called MADD-4 (an ADAMTSL) that guides migrations along the dorsoventral axis of the nematode Caenorhabditis elegans. We showed that the transmembrane receptor, UNC-40 (DCC), whose canonical ligand is the UNC-6 (netrin) guidance cue, is required for extension towards MADD-4. Here, we demonstrate that MADD-4 interacts with an EVA-1/UNC-40 co-receptor complex to attract cell extensions. EVA-1 is a conserved transmembrane protein with predicted galactose-binding lectin domains. EVA-1 functions in the same pathway as MADD-4, physically interacts with both MADD-4 and UNC-40, and enhances UNC-40''s sensitivity to the MADD-4 cue. This enhancement is especially important in the presence of UNC-6. In EVA-1''s absence, UNC-6 interferes with UNC-40''s responsiveness to MADD-4; in UNC-6''s absence, UNC-40''s responsiveness to MADD-4 is less dependent on EVA-1. By enabling UNC-40 to respond to MADD-4 in the presence of UNC-6, EVA-1 may increase the precision by which UNC-40-directed processes can reach their MADD-4-expressing targets within a field of the UNC-6 guidance cue.     

Methods to Develop an Electronic Medical Record Phenotype Algorithm to Compare the Risk of Coronary Artery Disease across 3 Chronic Disease Cohorts

Background

Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study.

Methods and Results

We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p<0.0001) after adjusting for traditional cardiovascular risk factors.

Conclusions

We developed and validated a CAD algorithm that performed well across diverse patient populations. The addition of NLP into the CAD algorithm improved the sensitivity of the algorithm, particularly in cohorts where the prevalence of CAD was low. Preliminary data suggest that CAD risk was significantly lower in RA and IBD compared to DM.     

Inactivation of chk2 and mus81 leads to impaired lymphocytes development, reduced genomic instability, and suppression of cancer

Chk2 is an effector kinase important for the activation of cell cycle checkpoints, p53, and apoptosis in response to DNA damage. Mus81 is required for the restart of stalled replication forks and for genomic integrity. Mus81(Δex3-4/Δex3-4) mice have increased cancer susceptibility that is exacerbated by p53 inactivation. In this study, we demonstrate that Chk2 inactivation impairs the development of Mus81(Δex3-4/Δex3-4) lymphoid cells in a cell-autonomous manner. Importantly, in contrast to its predicted tumor suppressor function, loss of Chk2 promotes mitotic catastrophe and cell death, and it results in suppressed oncogenic transformation and tumor development in Mus81(Δex3-4/Δex3-4) background. Thus, our data indicate that an important role for Chk2 is maintaining lymphocyte development and that dual inactivation of Chk2 and Mus81 remarkably inhibits cancer.     

Vertebrate codon bias indicates a highly GC-rich ancestral genome

Two factors are thought to have contributed to the origin of codon usage bias in eukaryotes: 1) genome-wide mutational forces that shape overall GC-content and create context-dependent nucleotide bias, and 2) positive selection for codons that maximize efficient and accurate translation. Particularly in vertebrates, these two explanations contradict each other and cloud the origin of codon bias in the taxon. On the one hand, mutational forces fail to explain GC-richness (~ 60%) of third codon positions, given the GC-poor overall genomic composition among vertebrates (~ 40%). On the other hand, positive selection cannot easily explain strict regularities in codon preferences. Large-scale bioinformatic assessment, of nucleotide composition of coding and non-coding sequences in vertebrates and other taxa, suggests a simple possible resolution for this contradiction. Specifically, we propose that the last common vertebrate ancestor had a GC-rich genome (~ 65% GC). The data suggest that whole-genome mutational bias is the major driving force for generating codon bias. As the bias becomes prominent, it begins to affect translation and can result in positive selection for optimal codons. The positive selection can, in turn, significantly modulate codon preferences.     

MED12 somatic mutations encompassing exon 2 associated with benign breast fibroadenomas and not breast carcinoma in Indian women

Fibroadenoma is the most common type of benign breast tumor, accounting for 90% of benign lesions in India. Somatic mutations in the mediator complex subunit 12 (MED12) gene play a critical role in fibroepithelial tumorigenesis. The current study evaluated the hotspot region encompassing exon 2 of the MED12 gene, in benign and malignant breast tumor tissue from women who presented for breast lump evaluation. A total of 100 (80 fibroadenoma and 20 breast cancer) samples were analyzed by polymerase chain reaction-Sanger sequencing. Sequence variant analysis showed that 68.75% of nucleotide changes were found in exon 2 and the remaining in the adjacent intron 1. Codon 44 was implicated as a hotspot mutation in benign tumors, and 86.36% of the identified mutations involved this codon. An in silico functional analysis of missense mutations using consensus scoring sorting intolerant from tolerant (SIFT), SIFT seq, Polyphen2, Mutation Assessor, SIFT transFIC, Polyphen2 transFIC, Mutation Assesor transFIC, I-Mutant, DUET, PON-PS, SNAP2, and protein variation effect analyzer] revealed that apart from variants involving codon 44 (G44S; G44H), others like V41A and E55D were also predicted to be deleterious. Most of the missense mutations appeared in the loop region of the MED12 protein, which is expected to affect its functional interaction with cyclin C–CDK8/CDK19, causing loss of mediator-associated cyclin depended kinase (CDK) activity. These results suggest a key role of MED12 somatic variations in the pathogenesis of fibroadenoma. For the first time, it was demonstrated that MED12 sequence variations are present in benign breast tumors in the south Indian population.     

Bioinformatics analysis of plant orthologous introns: identification of an intronic tRNA-like sequence

Orthologous introns have identical positions relative to the coding sequence in orthologous genes of different species. By analyzing the complete genomes of five plants we generated a database of 40,512 orthologous intron groups of dicotyledonous plants, 28,519 orthologous intron groups of angiosperms, and 15,726 of land plants (moss and angiosperms). Multiple sequence alignments of each orthologous intron group were obtained using the Mafft algorithm. The number of conserved regions in plant introns appeared to be hundreds of times fewer than that in mammals or vertebrates. Approximately three quarters of conserved intronic regions among angiosperms and dicots, in particular, correspond to alternatively-spliced exonic sequences. We registered only a handful of conserved intronic ncRNAs of flowering plants. However, the most evolutionarily conserved intronic region, which is ubiquitous for all plants examined in this study, including moss, possessed multiple structural features of tRNAs, which caused us to classify it as a putative tRNA-like ncRNA. Intronic sequences encoding tRNA-like structures are not unique to plants. Bioinformatics examination of the presence of tRNA inside introns revealed an unusually long-term association of four glycine tRNAs inside the Vac14 gene of fish, amniotes, and mammals.     

Prenatal skeletal dysplasia phenotype in severe MLII alpha/beta with novel GNPTAB mutation

We report a neonate who was diagnosed as a case of skeletal dysplasia during pregnancy, and was subsequently diagnosed as a case of MLII alpha/beta on the basis of clinical and radiological findings and molecular testing of the parents. A novel GNPTAB mutation c.1701delC [p.F566LfsX5] was identified in the father. The case reiterates the severe prenatal phenotype of MLII alpha/beta which mimics skeletal dysplasia and illustrates the utility of molecular genetic analysis in confirmation of diagnosis and subsequent genetic counselling.