The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at  https://github.com/dib-lab/khmer/.

Non-tumoural cells within the tumour microenvironment (TME) influence tumour proliferation, invasiveness and angiogenesis. Little is known about TME in pituitary neuroendocrine tumours (PitNETs). We aimed to characterise the role of TME in the aggressive behaviour of PitNETs, focusing on immune cells and cytokines. The cytokine secretome of 16 clinically non-functioning PitNETs (NF-PitNETs) and 8 somatotropinomas was assessed in primary culture using an immunoassay panel with 42 cytokines. This was correlated with macrophage (CD68, HLA-DR, CD163), T-lymphocyte (CD8, CD4, FOXP3), B-lymphocyte (CD20), neutrophil (neutrophil elastase) and endothelial cells (CD31) content, compared to normal pituitaries (NPs, n = 5). In vitro tumour–macrophage interactions were assessed by conditioned medium (CM) of GH3 (pituitary tumour) and RAW264.7 (macrophage) cell lines on morphology, migration/invasion, epithelial-to-mesenchymal transition and cytokine secretion. IL-8, CCL2, CCL3, CCL4, CXCL10, CCL22 and CXCL1 are the main PitNET-derived cytokines. PitNETs with increased macrophage and neutrophil content had higher IL-8, CCL2, CCL3, CCL4 and CXCL1 levels. CD8+ T-lymphocytes were associated to higher CCL2, CCL4 and VEGF-A levels. PitNETs had more macrophages than NPs (p < 0.001), with a 3-fold increased CD163:HLA-DR macrophage ratio. PitNETs contained more CD4+ T-lymphocytes (p = 0.005), but fewer neutrophils (p = 0.047) with a 2-fold decreased CD8:CD4 ratio. NF-PitNETs secreted more cytokines and had 9 times more neutrophils than somatotropinomas (p = 0.002). PitNETs with higher Ki-67 had more FOXP3+ T cells, as well as lower CD68:FOXP3, CD8:CD4 and CD8:FOXP3 ratios. PitNETs with “deleterious immune phenotype” (CD68hiCD4hiFOXP3hiCD20hi) had a Ki-67 ≥ 3%. CD163:HLA-DR macrophage ratio was positively correlated with microvessel density (p = 0.015) and area (p < 0.001). GH3 cell-CM increased macrophage chemotaxis, while macrophage-CM changed morphology, invasion, epithelial-to-mesenchymal transition and secreted cytokines of GH3 cells. PitNETs are characterised by increased CD163:HLA-DR macrophage and reduced CD8:CD4 and CD8:FOXP3 T cell ratios. PitNET-derived chemokines facilitate macrophage, neutrophil and T cell recruitment into the tumours which can determine aggressive behaviour.

The C57BL/6J and C57BL/6N mice have well-documented phenotypic and genotypic differences, including the infamous nicotinamide nucleotide transhydrogenase (Nnt) null mutation in the C57BL/6J substrain, which has been linked to cardiovascular traits in mice and cardiomyopathy in humans. To assess whether Nnt loss alone causes a cardiovascular phenotype, we investigated the C57BL/6N, C57BL/6J mice and a C57BL/6J-BAC transgenic rescuing NNT expression, at 3, 12, and 18 mo. We identified a modest dilated cardiomyopathy in the C57BL/6N mice, absent in the two B6J substrains. Immunofluorescent staining of cardiomyocytes revealed eccentric hypertrophy in these mice, with defects in sarcomere organisation. RNAseq analysis identified differential expression of a number of cardiac remodelling genes commonly associated with cardiac disease segregating with the phenotype. Variant calling from RNAseq data identified a myosin light chain kinase 3 (Mylk3) mutation in C57BL/6N mice, which abolishes MYLK3 protein expression. These results indicate the C57BL/6J Nnt-null mice do not develop cardiomyopathy; however, we identified a null mutation in Mylk3 as a credible cause of the cardiomyopathy phenotype in the C57BL/6N.