Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection

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Inactivation of rat pineal hydroxyindole-O-methyltransferase by disulfide-containing compounds

Rat pineal hydroxyindole-O-methyltransferase activity in crude homogenates is reduced by treatment with disulfides. Cystamine (IC50 = 128 microM) and selenocystamine (IC50 = 13 microM) are the most potent compounds tested. Reduced cystamine (cysteamine) and diaminohexane are inactive. N,N'-Diacetylcystamine, penicillamine disulfide, and glutathione disulfide are less potent or inactive; but several peptides (oxytocin, vasopressin, and arginine vasotocin) are active. Inactivation by cystamine is time- and temperature-dependent and is accelerated at higher pH. Disulfide treatment of intact pinealocytes also inactivates the enzyme. Addition of dithiothreitol during the enzyme assay completely reactivates inactivated enzyme formed by disulfide treatment of homogenates or intact cells. Rat hydroxyindole-O-methyltransferase is also inactivated in the absence of added disulfides and dissolved O2. This spontaneous inactivation is time-, temperature-, and pH-dependent and can be completely prevented, but not reversed, by dithiothreitol. In contrast to the inhibitory effects of cystamine on the rat enzyme, cystamine does not alter bovine hydroxyindole-O-methyltransferase and increases ovine hydroxyindole-O-methyltransferase activity. The bovine and ovine enzymes do not become inactive in the absence of added disulfides. Together these observations indicate that rat pineal hydroxyindole-O-methyltransferase can be inactivated by a protein thiol:disulfide exchange mechanism. This mechanism may contribute to the physiological regulation of this enzyme in the rat pineal gland but does not appear to be a common feature of pineal hydroxyindole-O-methyltransferase regulation in all species.     

Environmentally constrained mutation and adaptive evolution in Salmonella

The relationship between environment and mutation is complex [1]. Claims of Lamarkian mutation [2] have proved unfounded [3], [4] and [5]; it is apparent, however, that the external environment can influence the generation of heritable variation, through either direct effects on DNA sequence [6] or DNA maintenance and copying mechanisms [7], [8], [9] and [10], or as a consequence of evolutionary processes [11], [12], [13], [14], [15] and [16]. The spectrum of mutational events subject to environmental influence is unknown [6] and precisely how environmental signals modulate mutation is unclear. Evidence from bacteria suggests that a transient recombination-dependent hypermutational state can be induced by starvation [5]. It is also apparent that chnages in the mutability of specific loci can be influenced by alterations in DNA topology [10] and [17]. Here we describe a remarkable instance of adaptive evolution in Salmonella which is caused by a mutation that occurs in intermediate-strength osmotic environments. We show that the mutation is not ‘directed’ and describe its genetic basis. We also present compelling evidence in support of the hypothesis that the mutational event is constrained by signals transmitted from the external environment via changes in the activity of DNA gyrase.     

Molecular alteration of a muscarinic acetylcholine receptor system during synaptogenesis

Biochemical properties of the muscarinic acetylcholine receptor system of the avian retina were found to change during the period when synapses form in ovo. Comparison of ligand binding to membranes obtained before and after synaptogenesis showed a significant increase in the affinity, but not proportion, of the high affinity agonist-binding state. There was no change in receptor sensitivity to antagonists during this period. Pirenzepine binding, which can discriminate muscarinic receptor subtypes, showed the presence of a single population of low affinity sites (M2) before and after synaptogenesis. The change in agonist binding was not due to the late development of receptor function; tests for receptor-stimulated phosphatidylinositol turnover and for modulation of agonist binding by guanylylimidodiphosphate showed functional coupling to be present several days prior to the onset of synapse formation. However, detergent-solubilization of membranes eliminated differences in agonist binding between receptors from embryos and hatched chicks, suggesting a developmental change in interactions of the receptor with functionally related membrane components. A possible basis for altered interactions was obtained from isoelectric point data showing that the muscarinic receptor population underwent a transition from a predominantly low pI form (4.25) in 13 day embryos to a predominantly high pI form (4.50) in newly hatched chicks. The possibility that biochemical changes in the muscarinic receptor play a role in differentiation of the system by controlling receptor position on the surface of nerve cells is discussed.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.