Identifying the optimal donor for natural killer cell adoptive therapy to treat paediatric B- and T-cell acute lymphoblastic leukaemia.

Objectives: Natural killer (NK) cells are an attractive source of cells for an 'off the shelf' cellular therapy because of their innate capacity to target malignant cells, and ability to be transferred between donors and patients. However, since not all NK cells are equally effective at targeting cancer, selecting the right donor for cellular therapy is critical for the success of the treatment. Recently, cellular therapies utilising NK cells from cytomegalovirus (CMV)-seropositive donors have been explored. However, whether these NK cells are the best source to treat paediatric acute lymphoblastic leukaemia (ALL) remains unclear. Methods: Using a panel of patient-derived paediatric B- and T-ALL, we assessed the ability of NK cells from 49 healthy donors to mount an effective functional response against these two major subtypes of ALL. Results: From this cohort, we have identified a pool of donors with superior activity against multiple ALL cells. While these donors were more likely to be CMV+, we identified multiple CMVneg donors within this group. Furthermore, NK cells from these donors recognised B- and T-ALL through different activating receptors. Dividing functional NK cells into 29 unique subsets, we observed that within each individual the same NK cell subsets dominated across all ALL cells. Intriguingly, this occurred despite the ALL cells in our panel expressing different combinations of NK cell ligands. Finally, we can demonstrate that cellular therapy products derived from these superior donors significantly delayed leukaemia progression in preclinical models of ALL. Conclusions: We have identified a pool of superior donors that are effective against a range of ALL cells, representing a potential pool of donors that can be used as an adoptive NK cell therapy to treat paediatric ALL

The Engaged University: Providing a Platform for Research That Transforms Society

Despite a growing recognition that the solutions to current environmental problems will be developed through collaborations between scientists and stakeholders, substantial challenges stifle such cooperation and slow the transfer of knowledge. Challenges occur at several levels, including individual, disciplinary, and institutional. All of these have implications for scholars working at academic and research institutions. Fortunately, creative ideas and tested models exist that provide opportunities for conversation and serious consideration about how such institutions can facilitate the dialogue between scientists and societ

Two new rapid SNP-typing methods for classifying Mycobacterium tuberculosis complex into the main phylogenetic lineages

There is increasing evidence that strain variation in Mycobacterium tuberculosis complex (MTBC) might influence the outcome of tuberculosis infection and disease. To assess genotype-phenotype associations, phylogenetically robust molecular markers and appropriate genotyping tools are required. Most current genotyping methods for MTBC are based on mobile or repetitive DNA elements. Because these elements are prone to convergent evolution, the corresponding genotyping techniques are suboptimal for phylogenetic studies and strain classification. By contrast, single nucleotide polymorphisms (SNP) are ideal markers for classifying MTBC into phylogenetic lineages, as they exhibit very low degrees of homoplasy. In this study, we developed two complementary SNP-based genotyping methods to classify strains into the six main human-associated lineages of MTBC, the 'Beijing' sublineage, and the clade comprising Mycobacterium bovis and Mycobacterium caprae. Phylogenetically informative SNPs were obtained from 22 MTBC whole-genome sequences. The first assay, referred to as MOL-PCR, is a ligation-dependent PCR with signal detection by fluorescent microspheres and a Luminex flow cytometer, which simultaneously interrogates eight SNPs. The second assay is based on six individual TaqMan real-time PCR assays for singleplex SNP-typing. We compared MOL-PCR and TaqMan results in two panels of clinical MTBC isolates. Both methods agreed fully when assigning 36 well-characterized strains into the main phylogenetic lineages. The sensitivity in allele-calling was 98.6% and 98.8% for MOL-PCR and TaqMan, respectively. Typing of an additional panel of 78 unknown clinical isolates revealed 99.2% and 100% sensitivity in allele-calling, respectively, and 100% agreement in lineage assignment between both methods. While MOL-PCR and TaqMan are both highly sensitive and specific, MOL-PCR is ideal for classification of isolates with no previous information, whereas TaqMan is faster for confirmation. Furthermore, both methods are rapid, flexible and comparably inexpensive

Identifying differential exon splicing using linear models and correlation coefficients

Background: With the availability of the Affymetrix exon arrays a number of tools have been developed to enable the analysis. These however can be expensive or have several pre-installation requirements. This led us to develop an analysis workflow for analysing differential splicing using freely available software packages that are already being widely used for gene expression analysis. The workflow uses the packages in the standard installation of R and Bioconductor (BiocLite) to identify differential splicing. We use the splice index method with the LIMMA framework. The main drawback with this approach is that it relies on accurate estimates of gene expression from the probe-level data. Methods such as RMA and PLIER may misestimate when a large proportion of exons are spliced. We therefore present the novel concept of a gene correlation coefficient calculated using only the probeset expression pattern within a gene. We show that genes with lower correlation coefficients are likely to be differentially spliced.Results: The LIMMA approach was used to identify several tissue-specific transcripts and splicing events that are supported by previous experimental studies. Filtering the data is necessary, particularly removing exons and genes that are not expressed in all samples and cross-hybridising probesets, in order to reduce the false positive rate. The LIMMA approach ranked genes containing single or few differentially spliced exons much higher than genes containing several differentially spliced exons. On the other hand we found the gene correlation coefficient approach better for identifying genes with a large number of differentially spliced exons.Conclusion: We show that LIMMA can be used to identify differential exon splicing from Affymetrix exon array data. Though further work would be necessary to develop the use of correlation coefficients into a complete analysis approach, the preliminary results demonstrate their usefulness for identifying differentially spliced genes. The two approaches work complementary as they can potentially identify different subsets of genes (single/few spliced exons vs. large transcript structure differences)

Radiocarbon-Based Partitioning of Soil Respiration in an Old-Growth Coniferous Forest

Temperate forests play an important role in the global carbon cycle, and are thought to currently be a sink for atmospheric CO₂. However, we lack understanding of the drivers of forest carbon accumulation and loss, hampering our ability to predict carbon cycle responses to global change. In this study, we used CO₂ flux and radiocarbon (¹⁴C) measurements to investigate the role of seasonal drivers on soil respiration. Radiocarbon measurements of CO₂ evolved during incubation of fine roots and root-free soils at the beginning and end of the growing season (April and August) showed that these two soil respiration sources (fine roots vis-a`-vis soils) have different mean residence times that stayed constant between seasons. Radiocarbon measurements show that root respiration was made up of carbon fixed 3–5 years prior to sampling, and that heterotrophic respiration was made up of carbon fixed 7–10 years prior. The difference in radiocarbon signature between the two sources allowed us to partition autotrophic and heterotrophic respiration sources for soil respiration measurements in the field. We observed a small but significant increase in Δ¹⁴C of soil respiration between April and August, suggesting an increase in heterotrophic respiration sources over the growing season. Using a two end-member mixing model, we estimate that 55 ± 22% of soil respiration originated from autotrophic (root) sources in April, but their contribution dropped to 38 ± 21% in August. These findings suggest that the contribution of root respiration increases at a time of high productivity and/or as a result of relatively low microbial respiration in the early spring in this old-growth coniferous forest.Keywords: root respiration, stored carbon, residence time of soil carbon, photosynthates, soil CO₂ flux, radiocarbo

Specific and Sensitive Detection of H. pylori in Biological Specimens by Real-Time RT-PCR and In Situ Hybridization

PCR detection of H. pylori in biological specimens is rendered difficult by the extensive polymorphism of H. pylori genes and the suppressed expression of some genes in many strains. The goal of the present study was to (1) define a domain of the 16S rRNA sequence that is both highly conserved among H. pylori strains and also specific to the species, and (2) to develop and validate specific and sensitive molecular methods for the detection of H. pylori. We used a combination of in silico and molecular approaches to achieve sensitive and specific detection of H. pylori in biologic media. We sequenced two isolates from patients living in different continents and demonstrated that a 546-bp domain of the H. pylori 16S rRNA sequence was conserved in those strains and in published sequences. Within this conserved sequence, we defined a 229-bp domain that is 100% homologous in most H. pylori strains available in GenBank and also is specific for H. pylori. This sub-domain was then used to design (1) a set of high quality RT-PCR primers and probe that encompassed a 76-bp sequence and included at least two mismatches with other Helicobacter sp. 16S rRNA; and (2) in situ hybridization antisense probes. The sensitivity and specificity of the approaches were then demonstrated by using gastric biopsy specimens from patients and rhesus monkeys. This H. pylori-specific region of the 16S rRNA sequence is highly conserved among most H. pylori strains and allows specific detection, identification, and quantification of this bacterium in biological specimens

Correction of Population Stratification in Large Multi-Ethnic Association Studies

The vast majority of genetic risk factors for complex diseases have, taken individually, a small effect on the end phenotype. Population-based association studies therefore need very large sample sizes to detect significant differences between affected and non-affected individuals. Including thousands of affected individuals in a study requires recruitment in numerous centers, possibly from different geographic regions. Unfortunately such a recruitment strategy is likely to complicate the study design and to generate concerns regarding population stratification.We analyzed 9,751 individuals representing three main ethnic groups - Europeans, Arabs and South Asians - that had been enrolled from 154 centers involving 52 countries for a global case/control study of acute myocardial infarction. All individuals were genotyped at 103 candidate genes using 1,536 SNPs selected with a tagging strategy that captures most of the genetic diversity in different populations. We show that relying solely on self-reported ethnicity is not sufficient to exclude population stratification and we present additional methods to identify and correct for stratification.Our results highlight the importance of carefully addressing population stratification and of carefully “cleaning” the sample prior to analyses to obtain stronger signals of association and to avoid spurious results

Quantitative Assessment of Whole-Body Tumor Burden in Adult Patients with Neurofibromatosis

Patients with neurofibromatosis 1 (NF1), NF2, and schwannomatosis are at risk for multiple nerve sheath tumors and premature mortality. Traditional magnetic resonance imaging (MRI) has limited ability to assess disease burden accurately. The aim of this study was to establish an international cohort of patients with quantified whole-body internal tumor burden and to correlate tumor burden with clinical features of disease.We determined the number, volume, and distribution of internal nerve sheath tumors in patients using whole-body MRI (WBMRI) and three-dimensional computerized volumetry. We quantified the distribution of tumor volume across body regions and used unsupervised cluster analysis to group patients based on tumor distribution. We correlated the presence and volume of internal tumors with disease-related and demographic factors.WBMRI identified 1286 tumors in 145/247 patients (59%). Schwannomatosis patients had the highest prevalence of tumors (P = 0.03), but NF1 patients had the highest median tumor volume (P = 0.02). Tumor volume was unevenly distributed across body regions with overrepresentation of the head/neck and pelvis. Risk factors for internal nerve sheath tumors included decreasing numbers of café-au-lait macules in NF1 patients (P = 0.003) and history of skeletal abnormalities in NF2 patients (P = 0.09). Risk factors for higher tumor volume included female gender (P = 0.05) and increasing subcutaneous neurofibromas (P = 0.03) in NF1 patients, absence of cutaneous schwannomas in NF2 patients (P = 0.06), and increasing age in schwannomatosis patients (p = 0.10).WBMRI provides a comprehensive phenotype of neurofibromatosis patients, identifies distinct anatomic subgroups, and provides the basis for investigating molecular biomarkers that correlate with unique disease manifestations