Update on the human and mouse lipocalin (LCN) gene family, including evidence the mouse Mup cluster is result of an evolutionary bloom .

Lipocalins (LCNs) are members of a family of evolutionarily conserved genes present in all kingdoms of life. There are 19 LCN-like genes in the human genome, and 45 Lcn-like genes in the mouse genome, which include 22 major urinary protein (Mup) genes. The Mup genes, plus 29 of 30 Mup-ps pseudogenes, are all located together on chromosome (Chr) 4; evidence points to an evolutionary bloom that resulted in this Mup cluster in mouse, syntenic to the human Chr 9q32 locus at which a single MUPP pseudogene is located. LCNs play important roles in physiological processes by binding and transporting small hydrophobic molecules -such as steroid hormones, odorants, retinoids, and lipids-in plasma and other body fluids. LCNs are extensively used in clinical practice as biochemical markers. LCN-like proteins (18-40 kDa) have the characteristic eight β-strands creating a barrel structure that houses the binding-site; LCNs are synthesized in the liver as well as various secretory tissues. In rodents, MUPs are involved in communication of information in urine-derived scent marks, serving as signatures of individual identity, or as kairomones (to elicit fear behavior). MUPs also participate in regulation of glucose and lipid metabolism via a mechanism not well understood. Although much has been learned about LCNs and MUPs in recent years, more research is necessary to allow better understanding of their physiological functions, as well as their involvement in clinical disorders

Lipidomics and Redox Lipidomics Indicate Early Stage Alcohol-Induced Liver Damage.

Alcoholic fatty liver disease (AFLD) is characterized by lipid accumulation and inflammation and can progress to cirrhosis and cancer in the liver. AFLD diagnosis currently relies on histological analysis of liver biopsies. Early detection permits interventions that would prevent progression to cirrhosis or later stages of the disease. Herein, we have conducted the first comprehensive time-course study of lipids using novel state-of-the art lipidomics methods in plasma and liver in the early stages of a mouse model of AFLD, i.e., Lieber-DeCarli diet model. In ethanol-treated mice, changes in liver tissue included up-regulation of triglycerides (TGs) and oxidized TGs and down-regulation of phosphatidylcholine, lysophosphatidylcholine, and 20-22-carbon-containing lipid-mediator precursors. An increase in oxidized TGs preceded histological signs of early AFLD, i.e., steatosis, with these changes observed in both the liver and plasma. The major lipid classes dysregulated by ethanol play important roles in hepatic inflammation, steatosis, and oxidative damage. Conclusion: Alcohol consumption alters the liver lipidome before overt histological markers of early AFLD. This introduces the exciting possibility that specific lipids may serve as earlier biomarkers of AFLD than those currently being used

Dead enzymes in the aldehyde dehydrogenase gene family: role in drug metabolism and toxicology

<div><p><b><i>Introduction</i></b>: Dead enzymes are gene products (proteins) that lack key residues required for catalytic activity. In the pre-genome era, dead enzymes were thought to occur only rarely. However, they now have been shown to represent upwards of 10% of the total enzyme population in many families. The aldehyde dehydrogenase (ALDH) gene family encodes proteins that, depending on the isozyme, may be either catalytically-active or -inactive. Importantly, several ALDHs exhibit biological activities independent of their catalytic activity. For many of these, the physiological and pathophysiological functions remain to be established.</p><p><b><i>Areas covered</i>:</b> This article reviews the non-enzymatic functions of the ALDH superfamily. In addition, a search for additional non-catalytic ALDH records is undertaken. Our computational analyses reveal that there are currently 182 protein records (divided into 19 groups) that meet the criteria for dead enzymes.</p><p><b><i>Expert Opinion</i>:</b> Dead enzymes have the potential to exert biological actions through protein-protein interaction and allosteric modulation of the activity of an active enzyme. In addition, a dead enzyme may also influence availability of substrate for other active enzymes by sequestering substrate, and/or anchoring the substrate to a particular subcellular space. A large number of putatively non-catalytic ALDH proteins exist that warrant further study.</p></div

Update on the human and mouse lipocalin (LCN) gene family, including evidence the mouse Mup cluster is result of an “evolutionary bloom”

Abstract Lipocalins (LCNs) are members of a family of evolutionarily conserved genes present in all kingdoms of life. There are 19 LCN-like genes in the human genome, and 45 Lcn-like genes in the mouse genome, which include 22 major urinary protein (Mup) genes. The Mup genes, plus 29 of 30 Mup-ps pseudogenes, are all located together on chromosome (Chr) 4; evidence points to an “evolutionary bloom” that resulted in this Mup cluster in mouse, syntenic to the human Chr 9q32 locus at which a single MUPP pseudogene is located. LCNs play important roles in physiological processes by binding and transporting small hydrophobic molecules —such as steroid hormones, odorants, retinoids, and lipids—in plasma and other body fluids. LCNs are extensively used in clinical practice as biochemical markers. LCN-like proteins (18–40 kDa) have the characteristic eight β-strands creating a barrel structure that houses the binding-site; LCNs are synthesized in the liver as well as various secretory tissues. In rodents, MUPs are involved in communication of information in urine-derived scent marks, serving as signatures of individual identity, or as kairomones (to elicit fear behavior). MUPs also participate in regulation of glucose and lipid metabolism via a mechanism not well understood. Although much has been learned about LCNs and MUPs in recent years, more research is necessary to allow better understanding of their physiological functions, as well as their involvement in clinical disorders

Molecular Mechanisms of Alcohol-Induced Colorectal Carcinogenesis

The etiology of colorectal cancer (CRC) is complex. Approximately, 10% of individuals with CRC have predisposing germline mutations that lead to familial cancer syndromes, whereas most CRC patients have sporadic cancer resulting from a combination of environmental and genetic risk factors. It has become increasingly clear that chronic alcohol consumption is associated with the development of sporadic CRC; however, the exact mechanisms by which alcohol contributes to colorectal carcinogenesis are largely unknown. Several proposed mechanisms from studies in CRC models suggest that alcohol metabolites and/or enzymes associated with alcohol metabolism alter cellular redox balance, cause DNA damage, and epigenetic dysregulation. In addition, alcohol metabolites can cause a dysbiotic colorectal microbiome and intestinal permeability, resulting in bacterial translocation, inflammation, and immunosuppression. All of these effects can increase the risk of developing CRC. This review aims to outline some of the most significant and recent findings on the mechanisms of alcohol in colorectal carcinogenesis. We examine the effect of alcohol on the generation of reactive oxygen species, the development of genotoxic stress, modulation of one-carbon metabolism, disruption of the microbiome, and immunosuppression

Identification of dose-dependent DNA damage and repair responses from subchronic exposure to 1,4-dioxane in mice using a systems analysis approach

1,4-Dioxane (1,4-DX) is an environmental contaminant found in drinking water throughout the United States. Although it is a suspected liver carcinogen, there is no federal or state maximum contaminant level for 1,4-DX in drinking water. Very little is known about the mechanisms by which this chemical elicits liver carcinogenicity. In the present study, female BDF-1 mice were exposed to 1,4-DX (0, 50, 500, and 5,000 mg/L) in their drinking water for 1 or 4 weeks, to explore the toxic effects. Histopathological studies and a multi-omics approach (transcriptomics and metabolomics) were performed to investigate potential mechanisms of toxicity. Immunohistochemical analysis of the liver revealed increased H2AXγ-positive hepatocytes (a marker of DNA double-strand breaks), and an expansion of precholangiocytes (reflecting both DNA damage and repair mechanisms) after exposure. Liver transcriptomics revealed 1,4-DX-induced perturbations in signaling pathways predicted to impact the oxidative stress response, detoxification, and DNA damage. Liver, kidney, feces, and urine metabolomic profiling revealed no effect of 1,4-DX exposure, and bile acid quantification in liver and feces similarly showed no effect of exposure. We speculate that the results may be reflective of DNA damage being counterbalanced by the repair response, with the net result being a null overall effect on the systemic biochemistry of the exposed mice. Our results show a novel approach for the investigation of environmental chemicals that do not elicit cell death but have activated the repair systems in response to 1,4-DX exposure

Yale School of Public Health Symposium on tissue imaging mass spectrometry: illuminating phenotypic heterogeneity and drug disposition at the molecular level

‘A picture is worth a thousand words’ is an idiom from the English language (‘borrowed’ from on old Chinese proverb) that conveys the notion that a complex idea can be succinctly and fully described by a single image. Never has this expression been truer than in the clinical and pharmaceutical arenas. Enormous strides have been made by the scientific community in the evolving field of biomedical imaging with the aim of representing and/or quantifying aspects of disease and drug action by using tools such as radiography, MRI, PET, and ultrasound. Yet linking the phenotypical data generated by these systems to the genome is a challenging task. Identifying the link between the mechanism of disease or failed drug response to the genome of an individual is difficult, because central pieces of information are missing. However, imaging mass spectrometry (IMS) can overcome this issue. IMS aims to detect the molecular constituents of the tissue; these can then be correlated with genome-related characteristics, such as gene expression patterns and possible mutations, and ultimately provide a phenotypic molecular link to the complex disease biology. The big data technology of IMS can generate spatial information of thousands of metabolites and proteins from within a tissue, facilitating a deeper understanding of the connections between the genome, phenotypic characteristics and the biological response. It is a technology that has the potential to serve as a segue between gene expression and observed biological signal