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1. $N$ -electron Slater determinants from nonunitary canonical transformations of fermion operators

   https://doi.org/10.1103/PhysRevA.86.052102  

   Jiménez-Hoyos, Carlos A. ; Rodríguez-Guzmán, R. ; Scuseria, Gustavo E. ( November 2012 , Physical Review A)
2. Comammox Nitrospira bacteria outnumber canonical nitrifiers irrespective of electron donor mode and availability in biofiltration systems

   https://doi.org/10.1093/femsec/fiac032  

   Vilardi, Katherine J ; Cotto, Irmarie ; Sevillano, Maria ; Dai, Zihan ; Anderson, Christopher L ; Pinto, Ameet ( April 2022 , FEMS Microbiology Ecology)

   Abstract Complete ammonia oxidizing bacteria coexist with canonical ammonia and nitrite oxidizing bacteria in a wide range of environments. Whether this is due to competitive or cooperative interactions, or a result of niche separation is not yet clear. Understanding the factors driving coexistence of nitrifiers is critical to manage nitrification processes occurring in engineered and natural ecosystems. In this study, microcosm-based experiments were used to investigate the impact of nitrogen source and loading on the population dynamics of nitrifiers in drinking water biofilter media. Shotgun sequencing of DNA followed by co-assembly and reconstruction of metagenome assembled genomes revealed clade A2 comammox bacteria were likely the primary nitrifiers within microcosms and increased in abundance over Nitrosomonas-like ammonia and Nitrospira-like nitrite oxidizing bacteria irrespective of nitrogen source type or loading. Changes in comammox bacterial abundance did not correlate with either ammonia or nitrite oxidizing bacterial abundance in urea-amended systems, where metabolic reconstruction indicated potential for cross-feeding between strict ammonia and nitrite oxidizers. In contrast, comammox bacterial abundance demonstrated a negative correlation with nitrite oxidizers in ammonia-amended systems. This suggests potentially weaker synergistic relationships between strict ammonia and nitrite oxidizers might enable comammox bacteria to displace strict nitrite oxidizers from complex nitrifying communities.
3. Non-canonical LexA proteins regulate the SOS response in the Bacteroidetes

   https://doi.org/10.1093/nar/gkab773  

   Sánchez-Osuna, Miquel ; Cortés, Pilar ; Lee, Mark ; Smith, Aaron T ; Barbé, Jordi ; Erill, Ivan ( October 2021 , Nucleic Acids Research)

   Abstract Lesions to DNA compromise chromosome integrity, posing a direct threat to cell survival. The bacterial SOS response is a widespread transcriptional regulatory mechanism to address DNA damage. This response is coordinated by the LexA transcriptional repressor, which controls genes involved in DNA repair, mutagenesis and cell-cycle control. To date, the SOS response has been characterized in most major bacterial groups, with the notable exception of the Bacteroidetes. No LexA homologs had been identified in this large, diverse and ecologically important phylum, suggesting that it lacked an inducible mechanism to address DNA damage. Here, we report the identification of a novel family of transcriptional repressors in the Bacteroidetes that orchestrate a canonical response to DNA damage in this phylum. These proteins belong to the S24 peptidase family, but are structurally different from LexA. Their N-terminal domain is most closely related to CI-type bacteriophage repressors, suggesting that they may have originated from phage lytic phase repressors. Given their role as SOS regulators, however, we propose to designate them as non-canonical LexA proteins. The identification of a new class of repressors orchestrating the SOS response illuminates long-standing questions regarding the origin and plasticity of this transcriptional network.
4. Diverse members of the Xylariales lack canonical mating-type regions

   https://doi.org/10.1016/j.fgb.2018.12.004  

   Robinson, Aaron J. ; Natvig, Donald O. ( January 2019 , Fungal Genetics and Biology)
5. Generalized Linear Models outperform commonly used canonical analysis in estimating spatial structure of presence/absence data

   https://doi.org/10.7717/peerj.9777  

   Carlos-Júnior, Lélis A. ; Creed, Joel C. ; Marrs, Rob ; Lewis, Rob J. ; Moulton, Timothy P. ; Feijó-Lima, Rafael ; Spencer, Matthew ( January 2020 , PeerJ)

   Background Ecological communities tend to be spatially structured due to environmental gradients and/or spatially contagious processes such as growth, dispersion and species interactions. Data transformation followed by usage of algorithms such as Redundancy Analysis (RDA) is a fairly common approach in studies searching for spatial structure in ecological communities, despite recent suggestions advocating the use of Generalized Linear Models (GLMs). Here, we compared the performance of GLMs and RDA in describing spatial structure in ecological community composition data. We simulated realistic presence/absence data typical of many β -diversity studies. For model selection we used standard methods commonly used in most studies involving RDA and GLMs. Methods We simulated communities with known spatial structure, based on three real spatial community presence/absence datasets (one terrestrial, one marine and one freshwater). We used spatial eigenvectors as explanatory variables. We varied the number of non-zero coefficients of the spatial variables, and the spatial scales with which these coefficients were associated and then compared the performance of GLMs and RDA frameworks to correctly retrieve the spatial patterns contained in the simulated communities. We used two different methods for model selection, Forward Selection (FW) for RDA and the Akaike Information Criterion (AIC) for GLMs. The performancemore »of each method was assessed by scoring overall accuracy as the proportion of variables whose inclusion/exclusion status was correct, and by distinguishing which kind of error was observed for each method. We also assessed whether errors in variable selection could affect the interpretation of spatial structure. Results Overall GLM with AIC-based model selection (GLM/AIC) performed better than RDA/FW in selecting spatial explanatory variables, although under some simulations the methods performed similarly. In general, RDA/FW performed unpredictably, often retaining too many explanatory variables and selecting variables associated with incorrect spatial scales. The spatial scale of the pattern had a negligible effect on GLM/AIC performance but consistently affected RDA’s error rates under almost all scenarios. Conclusion We encourage the use of GLM/AIC for studies searching for spatial drivers of species presence/absence patterns, since this framework outperformed RDA/FW in situations most likely to be found in natural communities. It is likely that such recommendations might extend to other types of explanatory variables.« less