Effects of CD2-associated protein deficiency on amyloid-β in neuroblastoma cells and in an APP transgenic mouse model

BACKGROUND: CD2-associated protein (CD2AP) is an SH3-containing scaffold adaptor protein which regulates the actin cytoskeleton. Recently, CD2AP was identified as a genetic risk factor for Alzheimer’s disease (AD) by several genome-wide association studies. One of the hallmarks of AD is the accumulation of aggregated forms of Amyloid-β (Aβ) in the brain. In humans, CD2AP AD susceptibility locus (rs9349407) is associated with an increased plaque burden. Aβ production is highly regulated by endocytosis and is influenced by lysosomal function. Lysosomal trafficking is influenced by CD2AP. In this study, we decreased CD2AP levels in N2a neuroblastoma cultures and PS1APP mice and analyzed Aβ levels and plaque burden. RESULTS: Our data show that suppressing CD2AP expression using shRNA in N2a-APP695 cells results in decreased cell membrane amyloid precursor protein, decreased Aβ release and a lower Aβ(42)/Aβ(40) ratio. CD2AP protein is expressed in the brain as detected by western blot, and the expression level is dependent on gene dosage. In 1-month old PS1APP mice, complete loss of CD2AP in brain resulted in a decreased Aβ(42)/Aβ(40) ratio in brain tissue lysates while there was no effect on Aβ deposition or accumulation in PS1APP mice expressing one copy of CD2AP. CONCLUSION: CD2-Associated Protein affects Aβ levels and Aβ(42)/Aβ(40) ratio in vitro. The effect of CD2-Associated Protein on Aβ metabolism is subtle in vivo

Reconstitution of long and short patch mismatch repair reactions using Saccharomyces cerevisiae proteins

This study demonstrates mismatch repair (MMR) reactions reconstituted in vitro with purified Saccharomyces cerevisiae proteins. Biochemical analysis of MMR in vitro showed that MMR required mispair binding by the MutS homolog 2–MutS homolog 6 complex and corresponded to the Exonuclease 1-dependent subpathway of MMR. The reactions observed involved the formation of long excision tracts whose length was consistent with the length of MMR-dependent gene conversion tracts in vivo. The availability of this reconstituted MMR reaction now allows the wealth of mutations affecting MMR generated from the genetic analysis of S. cerevisiae MMR mechanisms in vivo to be used in biochemical reconstitution studies whose ultimate goal is to reconstitute MMR linked to both DNA replication and recombination

Influence of the Alternative Sigma Factor RpoN on Global Gene Expression and Carbon Catabolism in Enterococcus faecalis V583

The alternative sigma factor σ54 has been shown to regulate the expression of a wide array of virulence-associated genes, as well as central metabolism, in bacterial pathogens. In Gram-positive organisms, the σ54 is commonly associated with carbon metabolism. In this study, we show that the Enterococcus faecalis alternative sigma factor σ54 (RpoN) and its cognate enhancer binding protein MptR are essential for mannose utilization and are primary contributors to glucose uptake through the Mpt phosphotransferase system. To gain further insight into how RpoN contributes to global transcriptional changes, we performed microarray transcriptional analysis of strain V583 and an isogenic rpoN mutant grown in a chemically defined medium with glucose as the sole carbon source. Transcripts of 340 genes were differentially affected in the rpoN mutant; the predicted functions of these genes mainly related to nutrient acquisition. These differentially expressed genes included those with predicted catabolite-responsive element (cre) sites, consistent with loss of repression by the major carbon catabolite repressor CcpA. To determine if the inability to efficiently metabolize glucose/mannose affected infection outcome, we utilized two distinct infection models. We found that the rpoN mutant is significantly attenuated in both rabbit endocarditis and murine catheter-associated urinary tract infection (CAUTI). Here, we examined a ccpA mutant in the CAUTI model and showed that the absence of carbon catabolite control also significantly attenuates bacterial tissue burden in this model. Our data highlight the contribution of central carbon metabolism to growth of E. faecalis at various sites of infection

Genomic landscape of TP53-mutated myeloid malignancies

TP53-mutated myeloid malignancies are associated with complex cytogenetics and extensive structural variants, which complicates detailed genomic analysis by conventional clinical techniques. We performed whole-genome sequencing (WGS) of 42 acute myeloid leukemia (AML)/myelodysplastic syndromes (MDS) cases with paired normal tissue to better characterize the genomic landscape of TP53-mutated AML/MDS. WGS accurately determines TP53 allele status, a key prognostic factor, resulting in the reclassification of 12% of cases from monoallelic to multihit. Although aneuploidy and chromothripsis are shared with most TP53-mutated cancers, the specific chromosome abnormalities are distinct to each cancer type, suggesting a dependence on the tissue of origin. ETV6 expression is reduced in nearly all cases of TP53-mutated AML/MDS, either through gene deletion or presumed epigenetic silencing. Within the AML cohort, mutations of NF1 are highly enriched, with deletions of 1 copy of NF1 present in 45% of cases and biallelic mutations in 17%. Telomere content is increased in TP53-mutated AMLs compared with other AML subtypes, and abnormal telomeric sequences were detected in the interstitial regions of chromosomes. These data highlight the unique features of TP53-mutated myeloid malignancies, including the high frequency of chromothripsis and structural variation, the frequent involvement of unique genes (including NF1 and ETV6) as cooperating events, and evidence for altered telomere maintenance

On the asymptotics of higher-dimensional partitions

We conjecture that the asymptotic behavior of the numbers of solid (three-dimensional) partitions is identical to the asymptotics of the three-dimensional MacMahon numbers. Evidence is provided by an exact enumeration of solid partitions of all integers <=68 whose numbers are reproduced with surprising accuracy using the asymptotic formula (with one free parameter) and better accuracy on increasing the number of free parameters. We also conjecture that similar behavior holds for higher-dimensional partitions and provide some preliminary evidence for four and five-dimensional partitions.Comment: 30 pages, 8 tables, 4 figures (v2) New data (63-68) for solid partitions added; (v3) published version, new subsection providing an unbiased estimate of the leading for the leading coefficient added, some tables delete

FADS2 Function Loss at the Cancer Hotspot 11q13 Locus Diverts Lipid Signaling Precursor Synthesis to Unusual Eicosanoid Fatty Acids

Background: Genes coding for the fatty acid desaturases (FADS1, 2, 3) localized at the cancer genomic hotspot 11q13 locus are required for the biosynthesis of 20 carbon polyunsaturated fatty acids (PUFA) that are direct eicosanoid precursors. In several cancer cell lines, FADS2 encoded D6 and D8 desaturation is not functional. Methodology/Principal Findings: Analyzing MCF7 cell fatty acids with detailed structural mass spectrometry, we show that in the absence of FADS2 activity, the FADS1 product D5-desaturase operates to produce 5,11,14–20:3 and 5,11,14,17–20:4. These PUFA are missing the 8–9 double bond of the eicosanoid signaling precursors arachidonic acid (5,8,11,14–20:4) and eicosapentaenoic acid (5,8,11,14,17–20:5). Heterologous expression of FADS2 restores D6 and D8-desaturase activity and normal eicosanoid precursor synthesis. Conclusions/Significance: The loss of FADS2-encoded activities in cancer cells shuts down normal PUFA biosynthesis, deleting the endogenous supply of eicosanoid and downstream docosanoid precursors, and replacing them with unusual butylene-interrupted fatty acids. If recapitulated in vivo, the normal eicosanoid and docosanoid cell signaling milieu would be depleted and altered due to reduction and substitution of normal substrates with unusual substrates, with unpredictable consequences for cellular communication

Phenotype Sequencing: Identifying the Genes That Cause a Phenotype Directly from Pooled Sequencing of Independent Mutants

Random mutagenesis and phenotype screening provide a powerful method for dissecting microbial functions, but their results can be laborious to analyze experimentally. Each mutant strain may contain 50–100 random mutations, necessitating extensive functional experiments to determine which one causes the selected phenotype. To solve this problem, we propose a “Phenotype Sequencing” approach in which genes causing the phenotype can be identified directly from sequencing of multiple independent mutants. We developed a new computational analysis method showing that 1. causal genes can be identified with high probability from even a modest number of mutant genomes; 2. costs can be cut many-fold compared with a conventional genome sequencing approach via an optimized strategy of library-pooling (multiple strains per library) and tag-pooling (multiple tagged libraries per sequencing lane). We have performed extensive validation experiments on a set of E. coli mutants with increased isobutanol biofuel tolerance. We generated a range of sequencing experiments varying from 3 to 32 mutant strains, with pooling on 1 to 3 sequencing lanes. Our statistical analysis of these data (4099 mutations from 32 mutant genomes) successfully identified 3 genes (acrB, marC, acrA) that have been independently validated as causing this experimental phenotype. It must be emphasized that our approach reduces mutant sequencing costs enormously. Whereas a conventional genome sequencing experiment would have cost $7,200 in reagents alone, our Phenotype Sequencing design yielded the same information value for only$1200. In fact, our smallest experiments reliably identified acrB and marC at a cost of only $110–$340

PDBe-KB: collaboratively defining the biological context of structural data

The Protein Data Bank in Europe - Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive

The Problem of Experience in the Study of Organizations

This paper deals with the fact that we cannot experience large organizations directly, in the same way as we can experience individuals or small groups, and that this non-experientiability has certain implications for our scientific theories of organizations. Whereas a science is animated by a constructive interplay of theory concepts and experience concepts, the study of organizations has been confined to theory concepts alone. Implications of this analysis for developing a science of organizations are considered.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68303/2/10.1177_017084069301400102.pd

Using Genomic Sequencing for Classical Genetics in E. coli K12

We here develop computational methods to facilitate use of 454 whole genome shotgun sequencing to identify mutations in Escherichia coli K12. We had Roche sequence eight related strains derived as spontaneous mutants in a background without a whole genome sequence. They provided difference tables based on assembling each genome to reference strain E. coli MG1655 (NC_000913). Due to the evolutionary distance to MG1655, these contained a large number of both false negatives and positives. By manual analysis of the dataset, we detected all the known mutations (24 at nine locations) and identified and genetically confirmed new mutations necessary and sufficient for the phenotypes we had selected in four strains. We then had Roche assemble contigs de novo, which we further assembled to full-length pseudomolecules based on synteny with MG1655. This hybrid method facilitated detection of insertion mutations and allowed annotation from MG1655. After removing one genome with less than the optimal 20- to 30-fold sequence coverage, we identified 544 putative polymorphisms that included all of the known and selected mutations apart from insertions. Finally, we detected seven new mutations in a total of only 41 candidates by comparing single genomes to composite data for the remaining six and using a ranking system to penalize homopolymer sequencing and misassembly errors. An additional benefit of the analysis is a table of differences between MG1655 and a physiologically robust E. coli wild-type strain NCM3722. Both projects were greatly facilitated by use of comparative genomics tools in the CoGe software package (http://genomevolution.org/)