Two novel Gram-stain-positive, aerobic, non-motile, and yellow-pigmented, irregular rod-shaped bacteria (JY.X269 and
JY.X270T) were isolated from the near-surface sediments of river in Qinghai Province, P. R. China (32°37′13″N, 96°05′37″E)
in July 2019. Both strains were shown to grow at 15–35 °C and pH 7.0–10.0, and in the presence of 0–6.0% (w/v) NaCl.
The 16S rRNA gene sequence analysis showed that the isolates were closely related to Ornithinimicrobium cavernae CFH
30183
T (98.6–98.8% 16S rRNA gene sequence similarity), O. ciconiae H23M54T
(98.5–98.6%) and O. murale 01-Gi-040T
(98.3–98.5%). The phylogenetic and phylogenomic trees based on the 16S rRNA gene and 537 core gene sequences, respectively,
revealed that the two strains formed a distinct cluster with the above three species. The digital DNA-DNA hybridization
(dDDH) and average nucleotide identity (ANI) values between our two isolates (JY.X269 and JY.X270T) and other
Ornithinimicrobium species were within the ranges of 19.0–23.9% and 70.8–80.4%, respectively, all below the respective
recommended 70.0% and 95–96% cutoff point. Furthermore, the major cellular fatty acids (> 10.0%) of strains JY.X269 and
JY.X270T were iso-C15:0, iso-C16:0, and summed feature 9. Strain JY.X270T contained MK-8(H4) and ornithine as the predominant
menaquinone and diagnostic diamino acid component within the cell wall teichoic acids. β-cryptoxanthin (
C40H56O) can
be extracted from strain JY.X270T, and its content is 6.3 μg/ml. Based on results from the phylogenetic, chemotaxonomic,
and phenotypic analyses, the two strains could be classified as a novel species of the genus Ornithinimicrobium, for which
the name Ornithinimicrobium cryptoxanthini sp. nov. is proposed (type strain JY.X270T = CGMCC 1.19147T = JCM 34882T).
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The environment is under siege from a variety of pollution
sources. Fecal pollution is especially harmful as it disperses
pathogenic bacteria into waterways. Unraveling origins of
mixed sources of fecal bacteria is difficult and microbial
source tracking (MST) in complex environments is still a
daunting task. Despite the challenges, the need for answers
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qPCR and next generation sequencing (NGS) technologies
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towards culture independent technologies, where communitybased
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tools may be useful to overcome some of the limitations of
community-based MST methods as they can give deep insight
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with different environments. Adoption of machine
learning (ML) algorithms, along with the metagenomic based
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automated platform. To compliment that, ML-based approaches
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