Inducible Arginase 1 Deficiency in Mice Leads to Hyperargininemia and Altered Amino Acid Metabolism

Arginase deficiency is a rare autosomal recessive disorder resulting from a loss of the liver arginase isoform, arginase 1 (ARG1), which is the final step in the urea cycle for detoxifying ammonia. ARG1 deficiency leads to hyperargininemia, characterized by progressive neurological impairment, persistent growth retardation and infrequent episodes of hyperammonemia. Using the Cre/loxP-directed conditional gene knockout system, we generated an inducible Arg1-deficient mouse model by crossing “floxed” Arg1 mice with CreER^T2 mice. The resulting mice (Arg-Cre) die about two weeks after tamoxifen administration regardless of the starting age of inducing the knockout. These treated mice were nearly devoid of Arg1 mRNA, protein and liver arginase activity, and exhibited symptoms of hyperammonemia. Plasma amino acid analysis revealed pronounced hyperargininemia and significant alterations in amino acid and guanidino compound metabolism, including increased citrulline and guanidinoacetic acid. Despite no alteration in ornithine levels, concentrations of other amino acids such as proline and the branched-chain amino acids were reduced. In summary, we have generated and characterized an inducible Arg1-deficient mouse model exhibiting several pathologic manifestations of hyperargininemia. This model should prove useful for exploring potential treatment options of ARG1 deficiency.     

Effects of predator type and alternative prey on mosquito egg raft predation and destruction

Hydrobiologia - Differences in habitat and diet between species are often associated with morphological differences. Habitat and trophic adaptation have therefore been proposed as important drivers...     

Determining clinically relevant features in cytometry data using persistent homology

Cytometry experiments yield high-dimensional point cloud data that is difficult to interpret manually. Boolean gating techniques coupled with comparisons of relative abundances of cellular subsets is the current standard for cytometry data analysis. However, this approach is unable to capture more subtle topological features hidden in data, especially if those features are further masked by data transforms or significant batch effects or donor-to-donor variations in clinical data. We present that persistent homology, a mathematical structure that summarizes the topological features, can distinguish different sources of data, such as from groups of healthy donors or patients, effectively. Analysis of publicly available cytometry data describing non-naïve CD8+ T cells in COVID-19 patients and healthy controls shows that systematic structural differences exist between single cell protein expressions in COVID-19 patients and healthy controls. We identify proteins of interest by a decision-tree based classifier, sample points randomly and compute persistence diagrams from these sampled points. The resulting persistence diagrams identify regions in cytometry datasets of varying density and identify protruded structures such as ‘elbows’. We compute Wasserstein distances between these persistence diagrams for random pairs of healthy controls and COVID-19 patients and find that systematic structural differences exist between COVID-19 patients and healthy controls in the expression data for T-bet, Eomes, and Ki-67. Further analysis shows that expression of T-bet and Eomes are significantly downregulated in COVID-19 patient non-naïve CD8+ T cells compared to healthy controls. This counter-intuitive finding may indicate that canonical effector CD8+ T cells are less prevalent in COVID-19 patients than healthy controls. This method is applicable to any cytometry dataset for discovering novel insights through topological data analysis which may be difficult to ascertain otherwise with a standard gating strategy or existing bioinformatic tools.     

Substrate specificities of lipases in view of kinetic resolution of unsaturated fatty acids

Several commercially available lipases have been evaluated with regard to their substrate specificity in the esterification of fatty acids having specific positions of cis double bonds, e.g. petroselinic acid (n-12 18:1), alpha-linolenic acid (n-3 18:3), gamma-linolenic acid (n-6 18:3), stearidonic acid (n-3 18:4), dihomogamma-linolenic acid (n-6 20:3), eicosapentaenoic acid (n-3 20:5) and docosahexaenoic acid (n-3 22:6), with n-butanol. A common feature of most lipases, e.g. those from Penicillium cyclopium, Candida cylindracea, Mucor miehei, Rhizopus arrhizus and Penicillium sp. is that fatty acids having the first double bond from the carboxyl end as a cis-4 (n-3 22:6), cis-6 (n-12 18:1, n-6 18:3, n-3 18:4) or a cis-8 (n-6 20:3) double bond are strongly discriminated against compared to the other fatty acids, such as myristic acid (14:0), the reference standard, and n-3 18:3. In the case of the lipase from porcine pancreas, however, the discrimination against the above fatty acids is not as strong as with the other lipases. In contrast, the lipase from Chromobacterium viscosum shows a preference for n-12 18:1, n-6 18:3 and n-3 18:4. The observed substrate specificities can be utilized for enrichment of particular fatty acids by lipase-catalysed kinetic resolution from fatty acid mixtures, derived from naturally occurring fats and other lipids.Dedicated to Prof. David A. Walker, Robert Hill Institute, Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK, on the occasion of his sixty-fifth birthday on 18 August 1993 Correspondence to: K. D. Mukherjee     

Purification of and mechanism studies on citrate synthase. Use of biospecific adsorption-elution techniques.

Citrate synthases from animal tissues were found to bind to Sepharose-"ATP." A pure preparation of citrate synthase was obtained from a crude fraction of rat heart by the specific elution of the enzyme from the Sepharose-"ATP" with the dead end complex-forming substrates, oxalacetate and CoA. The proposed mechanisms of citrate synthase, obtained from steady state kinetics, were examined in light of the elution pattern of the enzyme obtained using combinations of substrates and substrate analogs.