Albumin 3′untranslated region facilitates increased recombinant protein production from Chinese hamster ovary cells

Chinese hamster ovary (CHO) cells are used for recombinant protein production in the pharmaceutical industry but there is a need to improve expression levels. In the present work experiments were carried out to test the effectiveness of different 3′untranslated regions (3′UTRs) in promoting production of a naturally secreted luciferase. Seamless cloning was used to produce expression vectors in which Gaussia princeps luciferase coding sequences were linked to the human albumin, immunoglobulin or chymotrypsinogen 3′UTR. Stably transfected CHO cells expressing these constructs were selected. Luciferase activity in the culture medium was increased 2–3‐fold by replacing the endogenous 3′UTR with the albumin 3′UTR and decreased by replacement with immunoglobulin or chymotrypsinogen 3′UTR. Replacement of the native 3′UTR with the albumin 3′UTR led to a 10‐fold increase in luciferase mRNA levels. Deletion analysis of the albumin 3′UTR showed that loss of nucleotides 1–50, which removed an AU‐rich complex stem loop region, caused significant reductions in both luciferase protein expression and luciferase mRNA levels. The results suggest that recombinant protein expression and yield could be improved by the careful selection of appropriate 3′UTR sequences.     

The Actin Binding Protein Adseverin Regulates Osteoclastogenesis

Adseverin (Ads), a member of the Gelsolin superfamily of actin binding proteins, regulates the actin cytoskeleton architecture by severing and capping existing filamentous actin (F-actin) strands and nucleating the assembly of new F-actin filaments. Ads has been implicated in cellular secretion, exocytosis and has also been shown to regulate chondrogenesis and megakaryoblastic leukemia cell differentiation. Here we report for the first time that Ads is involved in regulating osteoclastogenesis (OCG). Ads is induced during OCG downstream of RANK-ligand (RANKL) stimulation and is highly expressed in mature osteoclasts. The D5 isoform of Ads is not involved in regulating OCG, as its expression is not induced in response to RANKL. Three clonal Ads knockdown RAW264.7 (RAW) macrophage cell lines with varying degrees of Ads expression and OCG deficiency were generated. The most drastic OCG defect was noted in the clonal cell line with the greatest degree of Ads knockdown as indicated by a lack of TRAcP staining and multinucleation. RNAi mediated knockdown of Ads in osteoclast precursors resulted in distinct morphological changes characterized by altered F-actin distribution and increased filopodia formation. Ads knockdown precursor cells experienced enhanced migration while fusion of knockdown precursors cells was limited. Transient reintroduction of de novo Ads back into the knockdown system was capable of rescuing TRAcP expression but not osteoclast multinucleation most likely due to the transient nature of Ads expression. This preliminary study allows us to conclude that Ads is a RANKL induced early regulator of OCG with a potential role in pre-osteoclast differentiation and fusion.     

Ultra-large alignments using phylogeny-aware profiles

Many biological questions, including the estimation of deep evolutionary histories and the detection of remote homology between protein sequences, rely upon multiple sequence alignments and phylogenetic trees of large datasets. However, accurate large-scale multiple sequence alignment is very difficult, especially when the dataset contains fragmentary sequences. We present UPP, a multiple sequence alignment method that uses a new machine learning technique, the ensemble of hidden Markov models, which we propose here. UPP produces highly accurate alignments for both nucleotide and amino acid sequences, even on ultra-large datasets or datasets containing fragmentary sequences. UPP is available at https://github.com/smirarab/sepp.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0688-z) contains supplementary material, which is available to authorized users.     

Effect of Arbuscular Mycorrhizal Fungi On Yield and Phytoremediation Performance of Pot Marigold (Calendula officinalis L.) Under Heavy Metals Stress

In order to study the effect of mycorrhizal fungi (inoculated and non-inoculated) and heavy metals stress [0, Pb (150 and 300 mg/kg) and Cd (40 and 80 mg/kg)] on pot marigold (Calendula officinalis L.), a factorial experiment was conducted based on a randomized complete block design with 4 replications in Research Greenhouse of Department of Horticultural Sciences, University of Tehran, Iran, during 2012–2013. Plant height, herbal and flower fresh and dry weight, root fresh and dry weight and root volume, colonization percentage, total petal extract, total petal flavonoids, root and shoot P and K uptakes, and Pb and Cd accumulations in root and shoot were measured. Results indicated that with increasing soil Pb and Cd concentration, growth and yield of pot marigold was reduced significantly; Cd had greater negative impacts than Pb. However, mycorrhizal fungi alleviated these impacts by improving plant growth and yield. Pot marigold concentrated high amounts of Pb and especially Cd in its roots and shoots; mycorrhizal plants had a greater accumulation of these metals, so that those under 80 mg/kg Cd soil^?1 accumulated 833.3 and 1585.8 mg Cd in their shoots and roots, respectively. In conclusion, mycorrhizal fungi can improve not only growth and yield of pot marigold in heavy metal stressed condition, but also phytoremediation performance by increasing heavy metals accumulation in the plant organs.     

Microbial Community Response of an Organohalide Respiring Enrichment Culture to Permanganate Oxidation

While in situ chemical oxidation is often used to remediate tetrachloroethene (PCE) contaminated locations, very little is known about its influence on microbial composition and organohalide respiration (OHR) activity. Here, we investigate the impact of oxidation with permanganate on OHR rates, the abundance of organohalide respiring bacteria (OHRB) and reductive dehalogenase (rdh) genes using quantitative PCR, and microbial community composition through sequencing of 16S rRNA genes. A PCE degrading enrichment was repeatedly treated with low (25 μmol), medium (50 μmol), or high (100 μmol) permanganate doses, or no oxidant treatment (biotic control). Low and medium treatments led to higher OHR rates and enrichment of several OHRB and rdh genes, as compared to the biotic control. Improved degradation rates can be attributed to enrichment of (1) OHRB able to also utilize Mn oxides as a terminal electron acceptor and (2) non-dechlorinating community members of the Clostridiales and Deltaproteobacteria possibly supporting OHRB by providing essential co-factors. In contrast, high permanganate treatment disrupted dechlorination beyond cis-dichloroethene and caused at least a 2–4 orders of magnitude reduction in the abundance of all measured OHRB and rdh genes, as compared to the biotic control. High permanganate treatments resulted in a notably divergent microbial community, with increased abundances of organisms affiliated with Campylobacterales and Oceanospirillales capable of dissimilatory Mn reduction, and decreased abundance of presumed supporters of OHRB. Although OTUs classified within the OHR-supportive order Clostridiales and OHRB increased in abundance over the course of 213 days following the final 100 μmol permanganate treatment, only limited regeneration of PCE dechlorination was observed in one of three microcosms, suggesting strong chemical oxidation treatments can irreversibly disrupt OHR. Overall, this detailed investigation into dose-dependent changes of microbial composition and activity due to permanganate treatment provides insight into the mechanisms of OHR stimulation or disruption upon chemical oxidation.     

Application of a simple unstructured kinetic and cost of goods models to support T-cell therapy manufacture

Manufacturing of cell therapy products requires sufficient understanding of the cell culture variables and associated mechanisms for adequate control and risk analysis. The aim of this study was to apply an unstructured ordinary differential equation-based model for prediction of T-cell bioprocess outcomes as a function of process input parameters. A series of models were developed to represent the growth of T-cells as a function of time, culture volumes, cell densities, and glucose concentration using data from the Ambr®15 stirred bioreactor system. The models were sufficiently representative of the process to predict the glucose and volume provision required to maintain cell growth rate and quantitatively defined the relationship between glucose concentration, cell growth rate, and glucose utilization rate. The models demonstrated that although glucose is a limiting factor in batch supplied medium, a delivery rate of glucose at significantly less than the maximal specific consumption rate (0.05 mg 1 × 10⁶ cell h⁻¹) will adequately sustain cell growth due to a lower glucose Monod constant determining glucose consumption rate relative to the glucose Monod constant determining cell growth rate. The resultant volume and exchange requirements were used as inputs to an operational BioSolve cost model to suggest a cost-effective T-cell manufacturing process with minimum cost of goods per million cells produced and optimal volumetric productivity in a manufacturing settings. These findings highlight the potential of a simple unstructured model of T-cell growth in a stirred tank system to provide a framework for control and optimization of bioprocesses for manufacture.     

The impact of contaminants on the accuracy of genome skimming and the effectiveness of exclusion read filters

The ability to detect the identity of a sample obtained from its environment is a cornerstone of molecular ecological research. Thanks to the falling price of shotgun sequencing, genome skimming, the acquisition of short reads spread across the genome at low coverage, is emerging as an alternative to traditional barcoding. By obtaining far more data across the whole genome, skimming has the promise to increase the precision of sample identification beyond traditional barcoding while keeping the costs manageable. While methods for assembly‐free sample identification based on genome skims are now available, little is known about how these methods react to the presence of DNA from organisms other than the target species. In this paper, we show that the accuracy of distances computed between a pair of genome skims based on k‐mer similarity can degrade dramatically if the skims include contaminant reads; i.e., any reads originating from other organisms. We establish a theoretical model of the impact of contamination. We then suggest and evaluate a solution to the contamination problem: Query reads in a genome skim against an extensive database of possible contaminants (e.g., all microbial organisms) and filter out any read that matches. We evaluate the effectiveness of this strategy when implemented using Kraken‐II, in detailed analyses. Our results show substantial improvements in accuracy as a result of filtering but also point to limitations, including a need for relatively close matches in the contaminant database.     

Beyond DNA barcoding: The unrealized potential of genome skim data in sample identification

Genetic tools are increasingly used to identify and discriminate between species. One key transition in this process was the recognition of the potential of the ca 658bp fragment of the organelle cytochrome c oxidase I (COI) as a barcode region, which revolutionized animal bioidentification and lead, among others, to the instigation of the Barcode of Life Database (BOLD), containing currently barcodes from >7.9 million specimens. Following this discovery, suggestions for other organellar regions and markers, and the primers with which to amplify them, have been continuously proposed. Most recently, the field has taken the leap from PCR‐based generation of DNA references into shotgun sequencing‐based “genome skimming” alternatives, with the ultimate goal of assembling organellar reference genomes. Unfortunately, in genome skimming approaches, much of the nuclear genome (as much as 99% of the sequence data) is discarded, which is not only wasteful, but can also limit the power of discrimination at, or below, the species level. Here, we advocate that the full shotgun sequence data can be used to assign an identity (that we term for convenience its “DNA‐mark”) for both voucher and query samples, without requiring any computationally intensive pretreatment (e.g. assembly) of reads. We argue that if reference databases are populated with such “DNA‐marks,” it will enable future DNA‐based taxonomic identification to complement, or even replace PCR of barcodes with genome skimming, and we discuss how such methodology ultimately could enable identification to population, or even individual, level.     

Prevalence of bacteriocin activities and bacteriocin-encoding genes in enterococcal clinical isolates in Iran

The aim of the project was to isolate and characterize bacteriocin-producing enterococci, as well as determine the prevalence of enterocin structural genes in 187 enterococcal clinical isolates from the northwest of Iran. The isolates were screened for antibacterial activity against 15 different indicator strains. The proteinaceous nature of the antimicrobial substances was confirmed by sensitivity to proteinase K; their stability to heat treatment was tested at 60 °C and 100 °C for 20 and 10 min, respectively. The PCR method was applied to detect previously identified enterocin genes. Our results showed that 38 (20.3%) of the enterococcal isolates were considered to be potential bacteriocinogenic strains. Furthermore, genes encoding diverse bacteriocin are highly distributed among clinical enterococci, and the strains with multi-bacteriocin genes displayed high antimicrobial activity. Enterocin A, enterolysin A, and enterocin L50A/B were the most abundant structural genes detected in bacteriocinogenic strains. This work is the first survey on the prevalence of bacteriocin genes among clinical enterococci in Iran that has isolated a strain with high antimicrobial activity and sensitivity to clinically relevant antibiotics.     

Beta-blocker use and COPD mortality: a systematic review and meta-analysis

Background

Diagnostic and treatment approaches for sarcoidosis have changed dramatically over the past decade. Yet, the most recent reports of trends in hospitalizations of sarcoidosis patients are over ten years old. The objectives of this study were to determine the incidence of sarcoidosis among hospitalized patients and to analyze recent trends and seasonality of hospitalizations in sarcoidosis patients.

Methods

We performed a retrospective cohort study of the Nationwide Inpatient Sample from 1998 through 2008. We identified all hospitalizations with a primary or secondary diagnosis of sarcoidosis (ICD-9-CM code 135). Incidence was modeled as a seasonal time series about a linear trend.

Results

Time series analysis of the monthly number of hospitalizations revealed a distinct positive linear trend. Over the study period, the number of hospitalized patients with sarcoidosis increased from 37,516 to 70,947 cases. Trends were most pronounced in patients older than 55?years (p?<?0.0001), African Americans (p?<?0.0001), females (p?=?0.0289), and non-Medicaid populations (p?<?0.0001). Hospitalizations are seasonal with highest incidence in January through March.

Conclusions

Hospitalizations among sarcoidosis patients have almost doubled during the past decade, with disproportionate rate increases in African Americans, women, and older patients. The rate also increases among patients with insurance other than Medicaid. This study indicates the need for heightened surveillance of sarcoidosis patients given the unknown consequences of evolving treatment approaches. Our results point to a need for research investigating risk factors for hospitalization, including medications, co-morbidities, demographics, and socioeconomic status.