Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequenced 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. A phylogenetic analysis including thousands of globally sampled sequences allowed us to infer multiple independent introductions into Israel, followed by local transmission. Returning travelers from the U.S. contributed dramatically more to viral spread relative to their proportion in incoming infected travelers. Using phylodynamic analysis, we estimated that the basic reproduction number of the virus was initially around ~2.0-2.6, dropping by two-thirds following the implementation of social distancing measures. A comparison between reported and model-estimated case numbers indicated high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 1-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings underscore the ability of this virus to efficiently transmit between and within countries, as well as demonstrate the effectiveness of social distancing measures for reducing its spread.

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Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequence 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. We find that travelers returning from the United States of America significantly contributed to viral spread in Israel, more than their proportion in incoming infected travelers. Using phylodynamic analysis, we estimate that the basic reproduction number of the virus was initially around 2.5, dropping by more than two-thirds following the implementation of social distancing measures. We further report high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 2-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings demonstrate the effectiveness of social distancing measures for reducing viral spread.

In some immunocompromised patients with chronic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, considerable adaptive evolution occurs. Some substitutions found in chronic infections are lineage-defining mutations in variants of concern (VOCs), which has led to the hypothesis that VOCs emerged from chronic infections. In this study, we searched for drivers of VOC-like emergence by consolidating sequencing results from a set of 27 chronic infections. Most substitutions in this set reflected lineage-defining VOC mutations; however, a subset of mutations associated with successful global transmission was absent from chronic infections. We further tested the ability to associate antibody evasion mutations with patient-specific and virus-specific features and found that viral rebound is strongly correlated with the emergence of antibody evasion. We found evidence for dynamic polymorphic viral populations in most patients, suggesting that a compromised immune system selects for antibody evasion in particular niches in a patient’s body. We suggest that a tradeoff exists between antibody evasion and transmissibility and that extensive monitoring of chronic infections is necessary to further understanding of VOC emergence.

Edited by Ruma Banerjee Methyl coenzyme M reductase (MCR) catalyzes the last step in the biological production of methane by methanogenic archaea, as well as the first step in the anaerobic oxidation of methane to methanol by methanotrophic archaea. MCR contains a number of unique post-translational modifications in its ␣ subunit, including thioglycine, 1-N-methylhistidine, S-methylcysteine, 5-C-(S)-methylarginine, and 2-C-(S)-methylglutamine. Recently, genes responsible for the thioglycine and methylarginine modifications have been identified in bioinformatics studies and in vivo complementation of select mutants; however, none of these reactions has been verified in vitro. Herein, we purified and biochemically characterized the radical S-adenosylmethionine (SAM) protein MaMmp10, the product of the methanogenesis marker protein 10 gene in the methaneproducing archaea Methanosarcina acetivorans. Using an array of approaches, including kinetic assays, LC-MS-based quantification, and MALDI TOF-TOF MS analyses, we found that MaMmp10 catalyzes the methylation of the equivalent of Arg 285 in a peptide substrate surrogate, but only in the presence of cobalamin. We noted that the methyl group derives from SAM, with cobalamin acting as an intermediate carrier, and that MaMmp10 contains a C-terminal cobalamin-binding domain. Given that Mmp10 has not been annotated as a cobalamin-binding protein, these findings suggest that cobalamin-dependent radical SAM proteins are more prevalent than previously thought. Methyl coenzyme M reductase (MCR) 2 catalyzes the final and rate-limiting step in methanogenesis, which is the conver

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The biosynthetic route for homocysteine, intermediate in methionine biosynthesis, is unknown in some methanogenic archaea because homologues of the canonical required genes cannot be identified. Here we demonstrate that Methanocaldococcus jannaschii can biosynthesize homocysteine from aspartate semialdehyde and hydrogen sulfide. Additionally, we confirm the genes involved in this new pathway in Methanosarcina acetivorans. A possible series of reactions in which a thioaldehyde is formed and then reduced to a thiol are proposed. This represents a novel route for the biosynthesis of homocysteine and exemplifies unique aspects of sulfur chemistry occurring in prebiotic environments and in early life forms.

Echo state networks (ESNs) are a novel form of recurrent neural networks (RNNs) that provide an efficient and powerful computational model approximating nonlinear dynamical systems. A unique feature of an ESN is that a large number of neurons (the “reservoir”) are used, whose synaptic connections are generated randomly, with only the connections from the reservoir to the output modified by learning. Why a large randomly generated fixed RNN gives such excellent performance in approximating nonlinear systems is still not well understood. In this brief, we apply random matrix theory to examine the properties of random reservoirs in ESNs under different topologies (sparse or fully connected) and connection weights (Bernoulli or Gaussian). We quantify the asymptotic gap between the scaling factor bounds for the necessary and sufficient conditions previously proposed for the echo state property. We then show that the state transition mapping is contractive with high probability when only the necessary condition is satisfied, which corroborates and thus analytically explains the observation that in practice one obtains echo states when the spectral radius of the reservoir weight matrix is smaller than 1.