Phylogenetic and Evolutionary Patterns in Microbial Carotenoid Biosynthesis Are Revealed by Comparative Genomics

BACKGROUND: Carotenoids are multifunctional, taxonomically widespread and biotechnologically important pigments. Their biosynthesis serves as a model system for understanding the evolution of secondary metabolism. Microbial carotenoid diversity and evolution has hitherto been analyzed primarily from structural and biosynthetic perspectives, with the few phylogenetic analyses of microbial carotenoid biosynthetic proteins using either used limited datasets or lacking methodological rigor. Given the recent accumulation of microbial genome sequences, a reappraisal of microbial carotenoid biosynthetic diversity and evolution from the perspective of comparative genomics is warranted to validate and complement models of microbial carotenoid diversity and evolution based upon structural and biosynthetic data. METHODOLOGY/PRINCIPAL FINDINGS: Comparative genomics were used to identify and analyze in silico microbial carotenoid biosynthetic pathways. Four major phylogenetic lineages of carotenoid biosynthesis are suggested composed of: (i) Proteobacteria; (ii) Firmicutes; (iii) Chlorobi, Cyanobacteria and photosynthetic eukaryotes; and (iv) Archaea, Bacteroidetes and two separate sub-lineages of Actinobacteria. Using this phylogenetic framework, specific evolutionary mechanisms are proposed for carotenoid desaturase CrtI-family enzymes and carotenoid cyclases. Several phylogenetic lineage-specific evolutionary mechanisms are also suggested, including: (i) horizontal gene transfer; (ii) gene acquisition followed by differential gene loss; (iii) co-evolution with other biochemical structures such as proteorhodopsins; and (iv) positive selection. CONCLUSIONS/SIGNIFICANCE: Comparative genomics analyses of microbial carotenoid biosynthetic proteins indicate a much greater taxonomic diversity then that identified based on structural and biosynthetic data, and divides microbial carotenoid biosynthesis into several, well-supported phylogenetic lineages not evident previously. This phylogenetic framework is applicable to understanding the evolution of specific carotenoid biosynthetic proteins or the unique characteristics of carotenoid biosynthetic evolution in a specific phylogenetic lineage. Together, these analyses suggest a "bramble" model for microbial carotenoid biosynthesis whereby later biosynthetic steps exhibit greater evolutionary plasticity and reticulation compared to those closer to the biosynthetic "root". Structural diversification may be constrained ("trimmed") where selection is strong, but less so where selection is weaker. These analyses also highlight likely productive avenues for future research and bioprospecting by identifying both gaps in current knowledge and taxa which may particularly facilitate carotenoid diversification

Forbidden hugs in pandemic times: III. Observations of the luminous red nova AT 2021biy in the nearby galaxy NGC 4631

We present an observational study of the luminous red nova (LRN) AT 2021biy in the nearby galaxy NGC 4631. The field of the object was routinely imaged during the pre-eruptive stage by synoptic surveys, but the transient was detected only at a few epochs from ∼231 days before maximum brightness. The LRN outburst was monitored with unprecedented cadence both photometrically and spectroscopically. AT 2021biy shows a short-duration blue peak, with a bolometric luminosity of ∼1.6×1041 erg s-1, followed by the longest plateau among LRNe to date, with a duration of 210 days. A late-time hump in the light curve was also observed, possibly produced by a shell-shell collision. AT 2021biy exhibits the typical spectral evolution of LRNe. Early-time spectra are characterised by a blue continuum and prominent H emission lines. Then, the continuum becomes redder, resembling that of a K-type star with a forest of metal absorption lines during the plateau phase. Finally, late-time spectra show a very red continuum (TBB ≈ 2050 K) with molecular features (e.g., TiO) resembling those of M-type stars. Spectropolarimetric analysis indicates that AT 2021biy has local dust properties similar to those of V838 Mon in the Milky Way Galaxy. Inspection of archival Hubble Space Telescope data taken on 2003 August 3 reveals a ∼20 M⊙ progenitor candidate with log (L/L⊙) = 5.0 dex and Teff 5900 K at solar metallicity. The above luminosity and colour match those of a luminous yellow supergiant. Most likely, this source is a close binary, with a 17-24 M⊙ primary component

Some issues affecting the transcription of hungarian broadcast audio

International audienceThis paper reports on a speech-to-text (STT) transcription system for Hungarian broadcast audio developed for the 2012 Quaero evaluations. For this evaluation, no manually transcribed audio data were provided for model training, however a small amount of development data were provided to assess system performance. As a consequence, the acoustic models were developed in an unsupervised manner, with the only supervision provided indirectly by the language model. The language models were trained on texts downloaded from various websites, also without any speech transcripts. This contrasts with other STT systems for Hungarian broadcast audio which use at least 10 to 50 hours of manually transcribed data for acoustic training, and typically include speech transcripts in the language models. Based on mixed results previously reported applying morph-based approaches to agglutinative languages such as Hungarian, word-based language models were used. The initial Word Error Rate (WER) of the system using context-independent seed models from other languages of 59.8% on the 3h development corpus was reduced to 25.0% after successive training iterations and system refinement. The same system obtained a WER of 23.3% on the independent Quaero 2012 evaluation corpus (a mix of broadcast news and broadcast conversation data). These results compare well with previously reported systems on similar data. Various issues affecting system performance are discussed, such as amount of training data, the acoustic features and choice of text sources for language model training