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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to present with pulmonary and extra-pulmonary organ complications. In comparison with the 2009 pandemic (pH1N1), SARS-CoV-2 infection is likely to lead to more severe disease, with multi-organ effects, including cardiovascular disease. SARS-CoV-2 has been associated with acute and long-term cardiovascular disease, but the molecular changes govern this remain unknown.In this study, we investigated the landscape of cardiac tissues collected at rapid autopsy from SARS-CoV-2, pH1N1, and control patients using targeted spatial transcriptomics approaches. Although SARS-CoV-2 was not detected in cardiac tissue, host transcriptomics showed upregulation of genes associated with DNA damage and repair, heat shock, and M1-like macrophage infiltration in the cardiac tissues of COVID-19 patients. The DNA damage present in the SARS-CoV-2 patient samples, were further confirmed by γ−H2Ax immunohistochemistry. In comparison, pH1N1 showed upregulation of Interferon-stimulated genes (ISGs), in particular interferon and complement pathways, when compared with COVID-19 patients.These data demonstrate the emergence of distinct transcriptomic profiles in cardiac tissues of SARS-CoV-2 and pH1N1 influenza infection supporting the need for a greater understanding of the effects on extra-pulmonary organs, including the cardiovascular system of COVID-19 patients, to delineate the immunopathobiology of SARS-CoV-2 infection, and long term impact on health.

Natural Killer (NK) cells have long been considered an important part of the anti-tumor immune response due to their potent cytolytic and cytokine-secreting abilities. To date, a clear demonstration of the role NK cells play in human cancer is lacking, and there are still very few examples of therapies that efficiently exploit or enhance the spontaneous ability of NK cells to destroy the autologous cancer cells. Given the paradigm shift toward cancer immunotherapy over the past decade, there is a renewed push to understand how NK cell homeostasis and function are regulated in order to therapeutically harness these cells to treat cancer. This review will highlight recent advancements in our understanding of how growth factors impact on NK cell development, differentiation, survival and function with an emphasis on how these pathways may influence NK cell activity in the tumor microenvironment and control of cancer metastasis.

The project was funded in part by the Biotechnology and Biological Sciences Research Council (BB/HO1697X/1). S.E.H. was supported by a Nigel Groome PhD Studentship at Oxford Brookes University. S.E.H. was awarded a practical skills grant from the Society for Endocrinology and a travel grant from the Physiological Society to fund work at the University of Arizona.

Background Cancer outlier profile analysis (COPA) has proven to be an effective approach to analyzing cancer expression data, leading to the discovery of the TMPRSS2 and ETS family gene fusion events in prostate cancer. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. Here we present a modified outlier detection method, mCOPA, which contains refinements to the outlier-detection algorithm, identifies both over- and under-expressed outliers, is freely available, and can be applied to any expression dataset.

Recent advances in molecular technologies have opened up unprecedented opportunities for molecular ecologists to better understand the molecular basis of traits of ecological and evolutionary importance in almost any organism. Nevertheless, reliable and systematic inference of functionally relevant information from these masses of data remains challenging. The aim of this review is to highlight how the Gene Ontology (GO) database can be of use in resolving this challenge. The GO provides a largely species-neutral source of information on the molecular function, biological role and cellular location of tens of thousands of gene products. As it is designed to be species-neutral, the GO is well suited for cross-species use, meaning that, functional annotation derived from model organisms can be transferred to inferred orthologues in newly sequenced species. In other words, the GO can provide gene annotation information for species with nonannotated genomes. In this review, we describe the GO database, how functional information is linked with genes/gene products in model organisms, and how molecular ecologists can utilize this information to annotate their own data. Then, we outline various applications of GO for enhancing the understanding of molecular basis of traits in ecologically relevant species. We also highlight potential pitfalls, provide step-by-step recommendations for conducting a sound study in nonmodel organisms, suggest avenues for future research and outline a strategy for maximizing the benefits of a more ecological and evolutionary genomics-oriented ontology by ensuring its compatibility with the GO.

Background There is currently a shortage of human donor pancreata which limits the broad application of islet transplantation as a treatment for type 1 diabetes. Porcine islets have demonstrated potential as an alternative source, but a study evaluating islets from different donor ages under unified protocols has yet to be conducted. Methods Neonatal porcine islets (NPI; 1-3 days), juvenile porcine islets (JPI; 18-21 days), and adult porcine islets (API; 2+ years) were compared in vitro, including assessments of oxygen consumption rate, membrane integrity determined by FDA/PI staining, β-cell proliferation, dynamic glucose-stimulated insulin secretion, and RNA sequencing. Results Oxygen consumption rate normalized to DNA was not significantly different between ages. Membrane integrity was age dependent, and API had the highest percentage of intact cells. API also had the highest glucose-stimulated insulin secretion response during a dynamic insulin secretion assay and had 50-fold higher total insulin content compared to NPI and JPI. NPI and JPI had similar glucose responsiveness, β-cell percentage, and β-cell proliferation rate. Transcriptome analysis was consistent with physiological assessments. API transcriptomes were enriched for cellular metabolic and insulin secretory pathways, while NPI exhibited higher expression of genes associated with proliferation. Conclusions The oxygen demand, membrane integrity, β-cell function and proliferation, and transcriptomes of islets from API, JPI, and NPI provide a comprehensive physiological comparison for future studies. These assessments will inform the optimal application of each age of porcine islet to expand the availability of islet transplantation.

Protein-protein interactions (PPIs) underpin key biological processes in cells. Describing and interpreting this network of interactions is a key focus of computational systems biology. While mouse is commonly used as a model system for mammalian biology, the description of mouse PPIs available in public interaction databases is remarkably poor. Collectively, public resources such as BIND, IntACT and MINT contain only a few thousand mouse PPIs, far behind the many tens or hundreds of thousands likely to exist. To supplement this lack and to take advantage of other high-throughput omic data sets in mouse, here we identify that portion of the human interactome with orthologs in mouse, and from that infer a mouse interolog network. By inferring interactions in mouse based on only the most closely related species with abundant PPI data (human), we create a view of mouse interactions enriched for shared mammalian biological processes. We also demonstrate that available methods for determining orthologs between even closely related species produce distinctly different results, and we propose an integrated view of mouse-human orthology from which to infer a broader interolog network.

Application of a computational membrane organization prediction pipeline, MemO, identified putative type II membrane proteins as proteins predicted to encode a single alpha-helical transmembrane domain (TMD) and no signal peptides. MemO was applied to RIKEN's mouse isoform protein set to identify 1436 non-overlapping genomic regions or transcriptional units (TUs), which encode exclusively type II membrane proteins. Proteins with overlapping predicted InterPro and TMDs were reviewed to discard false positive predictions resulting in a dataset comprised of 1831 transcripts in 1408 TUs. This dataset was used to develop a systematic protocol to document subcellular localization of type II membrane proteins. This approach combines mining of published literature to identify subcellular localization data and a high-throughput, polymerase chain reaction (PCR)-based approach to experimentally characterize subcellular localization. These approaches have provided localization data for 244 and 169 proteins. Type II membrane proteins are localized to all major organelle compartments; however, some biases were observed towards the early secretory pathway and punctate structures. Collectively, this study reports the subcellular localization of 26% of the defined dataset. All reported localization data are presented in the LOCATE database (http://www.locate.imb.uq.edu.au).

The term "secretome" has been defined as a set of secreted proteins (Grimmond et al. [2003] Genome Res 13:1350-1359). The term "secreted protein" encompasses all proteins exported from the cell including growth factors, extracellular proteinases, morphogens, and extracellular matrix molecules. Defining the genes encoding secreted proteins that change in expression during organogenesis, the dynamic secretome, is likely to point to key drivers of morphogenesis. Such secreted proteins are involved in the reciprocal interactions between the ureteric bud (UB) and the metanephric mesenchyme (MM) that occur during organogenesis of the metanephros. Some key metanephric secreted proteins have been identified, but many remain to be determined. In this study, microarray expression profiling of E10.5, E11.5, and E13.5 kidney and consensus bioinformatic analysis were used to define a dynamic secretome of early metanephric development. In situ hybridisation was used to confirm microarray results and clarify spatial expression patterns for these genes. Forty-one secreted factors were dynamically expressed between the E10.5 and E13.5 timeframe profiled, and 25 of these factors had not previously been implicated in kidney development. A text-based anatomical ontology was used to spatially annotate the expression pattern of these genes in cultured metanephric explants.

A cDNA encoding pinto bean α-D-galactosidase [E.C. 3.2.1.22] was obtained by amplification of cDNA using highly conserved sequences found in eucaryotic α-D-galactosidases. Subsequently a full length Phaseolus cDNA clone was obtained that is 1537 nt long and contains untranslated 5′ and 3′ sequences. The nucleotide sequence of the cDNA has a high degree of homology with other eucaryotic (α-D-galactosidase genes. The recombinant α-D-galactosidase (rGal) was expressed in Escherichia coli and purified by ion exchange and affinity chromatography. Purified rGal was homogeneous by SDS-PAGE and had relative masses of 40.1 and 45.4 kDa under nonreducing and reducing conditions, respectively. The N-terminal sequence of the expressed protein contained the sequence GNGLGQTPPMG corresponding to that deduced from the cDNA sequence. The native molecular weight for rGal was determined to be 32.18 kDa by Sephacryl S-200 chromatography. The specific activity of the rGal was 349 μmoles of PNP-α-D-galactopyranoside hydrolyzed per mg of pure rGal per min. rGal was highly specific for α-D-galactosyl residues and degraded B oligosaccharide. No detectable hemagglutinin or protease activity was present in the preparations. Furthermore, rGal was active against the blood group B antigen on native human erythrocytes in cell suspension assays. The only detectable RBC phenotypic change was loss of the B and P1 epitopes. Recombinant Phaseolus vulgaris α-D-galactosidase may have useful biotechnical applications in the potential mass production of enzymatically converted, universally transfusable type O RBCs. α-D-galactosidase [E.C. 3.2.1.22] has been purified from a variety of procaryotic and eucaryotic species (1,2,3,4). Most α-D-galactosidases have similar low molecular weight substrate specificities, but activity against high molecular weight substrates is variable (5,6). Terminal α-D-galactoside residues are present in glycoproteins and glycolipids (7). Some α-D-galactosidases have activity against α-D-galactosyl residues on cell membrane glycoconjugates. Glycosidases with this property are useful for carbohydrate structural studies and biotechnical applications (8,9). Enzymes free of other glycosidase activities with activity near neutral pH are particularly useful for membrane modification studies on native cells. Complex sugar chains in glycolipids and glycoproteins have often been implicated in the growth and development of eucaryotes (10). In particular, complex sugar chains play an important role in the recognition of self in the immune system (11). Some α-D-galactosidases can modify certain carbohydrate membrane epitopes, thereby modulating the immune response. For example, the blood group B epitope expressed on erythrocytes contains a terminal α-D-galactosyl residue. Individuals lacking this antigen produce naturally occurring complement fixing antibodies to the B epitope (12). Hydrolysis of this terminal saccharide destroys the antigenic activity of the B determinant producing H antigen (blood type O) on erythrocytes (13). Only rare individuals produce clinically significant antibodies to the H antigen, and therefore, type O red blood cells are “universally” compatible and in great demand (14). Dhar purified α-D-galactosidase isozymes from Phaseolus vulgaris and characterized their activity (15). To our knowledge, our laboratory, in a brief report, is the first to describe the cloning of the gene and the use of recombinant enzyme for seroconverting blood type B to O cells (16). This paper describes the cloning, sequence, expression, purification, and characterization of recombinant α-D-galactosidase. Activity of the recombinant enzyme on the native human erythrocyte blood group B epitope is shown.