Gene expression patterns in ovarian carcinomas

We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers.     

Mathematical modeling of in vitro enzymatic production of 2-Keto-L-gulonic acid using NAD(H) or NADP(H) as cofactors

A 2-Keto-L-gulonic acid (2-KLG) production process using stationary Pantoea citrea cells and a Corynebacterium 2,5-diketo-D-gluconic acid (2,5-DKG) reductase enzyme has been developed which may represent an improved method of vitamin C biosynthesis. Experimental data was collected using the F22Y/A272G 2,5-DKG reductase mutant and NADP(H) as a cofactor. An extensive kinetic analysis was performed and a kinetic rate equation model for this process was developed. A recent protein engineering effort has resulted in several 2,5-DKG reductase mutants exhibiting improved activity with NADH as a cofactor. The use of NAD(H) in the bioreactor may be preferable due to its increased stability and lower cost. The kinetic parameters in the rate equation model have been replaced in order to predict 2-KLG production with NAD(H) as a cofactor. The model was also extended to predict 2-KLG production in the presence of a range of combined cofactor concentrations. This analysis suggests that the use of the F22Y/K232G/R238H/A272G 2,5-DKG reductase mutant with NAD(H) combined with a small amount of NADP(H) could provide a significant cost benefit for in vitro enzymatic 2-KLG production.     

New approaches for high-yield purification of Müllerian inhibiting substance improve its bioactivity

We have established a new method to purify Müllerian inhibiting substance (MIS) with higher purity and recovery over existing procedures. Recombinant human MIS was expressed in Chinese hamster ovary cells and secreted into chemically defined serum-free media. The secreted products were concentrated by either precipitation with ammonium sulfate or lectin-affinity chromatography, each of which was followed by anion-exchange chromatography. Further separation of the active carboxy-terminal domain of MIS was achieved after cleavage by plasmin followed by lectin-affinity chromatography. This method may be applicable to other members of the transforming growth factor beta family with which MIS shares sequence homology.     

Complete genome sequence of the orange-red pigmented, radioresistant Deinococcus proteolyticus type strain (MRP(T))

Deinococcus proteolyticus (ex Kobatake et al. 1973) Brook and Murray 1981 is one of currently 47 species in the genus Deinococcus within the family Deinococcaceae. Strain MRP(T) was isolated from feces of Lama glama and possesses extreme radiation resistance, a trait is shares with various other species of the genus Deinococcus, with D. proteolyticus being resistant up to 1.5 Mrad of gamma radiation. Strain MRP(T) is of further interest for its carotenoid pigment. The genome presented here is only the fifth completed genome sequence of a member of the genus Deinococcus (and the forth type strain) to be published, and will hopefully contribute to a better understanding of how members of this genus adapted to high gamma- or UV ionizing-radiation. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 2,886,836 bp long genome with its four large plasmids of lengths 97 kbp, 132 kbp, 196 kbp and 315 kbp harbors 2,741 protein-coding and 58 RNA genes and is a part of the Genomic Encyclopedia of Bacteria and Archaea project.     

Complete genome sequence of Methanoculleus marisnigri Romesser et al. 1981 type strain JR1

Methanoculleus marisnigri Romesser et al. 1981 is a methanogen belonging to the order Methanomicrobiales within the archaeal phylum Euryarchaeota. The type strain, JR1, was isolated from anoxic sediments of the Black Sea. M. marisnigri is of phylogenetic interest because at the time the sequencing project began only one genome had previously been sequenced from the order Methanomicrobiales. We report here the complete genome sequence of M. marisnigri type strain JR1 and its annotation. This is part of a Joint Genome Institute 2006 Community Sequencing Program to sequence genomes of diverse Archaea.     

Spatially resolved simulations of the spread of COVID-19 in three European countries

We explore the spatial and temporal spread of the novel SARS-CoV-2 virus under containment measures in three European countries based on fits to data of the early outbreak. Using data from Spain and Italy, we estimate an age dependent infection fatality ratio for SARS-CoV-2, as well as risks of hospitalization and intensive care admission. We use them in a model that simulates the dynamics of the virus using an age structured, spatially detailed agent based approach, that explicitly incorporates governmental interventions and changes in mobility and contact patterns occurred during the COVID-19 outbreak in each country. Our simulations reproduce several of the features of its spatio-temporal spread in the three countries studied. They show that containment measures combined with high density are responsible for the containment of cases within densely populated areas, and that spread to less densely populated areas occurred during the late stages of the first wave. The capability to reproduce observed features of the spatio-temporal dynamics of SARS-CoV-2 makes this model a potential candidate for forecasting the dynamics of SARS-CoV-2 in other settings, and we recommend its application in low and lower-middle income countries which remain understudied.     

WormFarm: a quantitative control and measurement device toward automated Caenorhabditis elegans aging analysis

Caenorhabditis elegans is a leading model organism for studying the basic mechanisms of aging. Progress has been limited, however, by the lack of an automated system for quantitative analysis of longevity and mean lifespan. To address this barrier, we developed ‘WormFarm’, an integrated microfluidic device for culturing nematodes. Cohorts of 30–50 animals are maintained throughout their lifespan in each of eight separate chambers on a single WormFarm polydimethylsiloxane chip. Design features allow for automated removal of progeny and efficient control of environmental conditions. In addition, we have developed computational algorithms for automated analysis of video footage to quantitate survival and other phenotypes, such as body size and motility. As proof‐of‐principle, we show here that WormFarm successfully recapitulates survival data obtained from a standard plate‐based assay for both RNAi‐mediated and dietary‐induced changes in lifespan. Further, using a fluorescent reporter in conjunction with WormFarm, we report an age‐associated decrease in fluorescent intensity of GFP in transgenic worms expressing GFP tagged with a mitochondrial import signal under the control of the myo‐3 promoter. This marker may therefore serve as a useful biomarker of biological age and aging rate.     

Evaluation of urinary trans-3′-hydroxycotinine as a biomarker of children's environmental tobacco smoke exposure

Abstract

The utility of urinary trans-3′-hydroxy cotinine (3HC) as a biomarker of environmental tobacco smoke (ETS) exposure was investigated in comparison with urinary cotinine (COT), the sum (3HC?+?COT), and ratio of the two nicotine metabolites (3HC/COT). Participants were 150 ETS exposed children (aged 1–44 months) and their parents. Child urine samples were collected during 3weekly baseline assessments and at interviews administered 3, 6, 12, and 18 months after baseline. Findings indicate that 3HC and COT can be measured reliably (rho?=?0.96, 0.88) and show equivalent levels of repeated measures stability (rho?=?0.71, 0.75). COT, 3HC, and 3HC?+?COT showed equally strong associations with air nicotine levels, reported ETS contamination, and reported ETS exposure (r=0.60–0.70). The intraclass correlations of 3HC/COT were lower than those for COT or 3HC. Older children had a higher 3HC/COT ratio than younger children (3.5 versus 2.2), and non-Hispanic White children had a higher ratio than African-American children (3.2 versus 1.9). These findings suggest that COT, 3HC, and 3HC?+?COT are approximately equivalent and equally strong biomarkers of ETS exposure in children. Moreover, 3HC/COT may provide a useful indicator to investigate age- and race-related differences in the metabolism of COT and 3HC.     

Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait''s genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function.