Larkinella punicea sp. nov., isolated from manganese mine soil

Microbial gene expression analysis of healthy and cancerous esophagus uncovers bacterial biomarkers of clinical outcomes

Local microbiome shifts are implicated in the development and progression of gastrointestinal cancers, and in particular, esophageal carcinoma (ESCA), which is among the most aggressive malignancies. Short-read RNA sequencing (RNAseq) is currently the leading technology to study gene expression changes in cancer. However, using RNAseq to study microbial gene expression is challenging. Here, we establish a new tool to efficiently detect viral and bacterial expression in human tissues through RNAseq. This approach employs a neural network to predict reads of likely microbial origin, which are targeted for assembly into longer contigs, improving identification of microbial species and genes. This approach is applied to perform a systematic comparison of bacterial expression in ESCA and healthy esophagi. We uncover bacterial genera that are over or underabundant in ESCA vs healthy esophagi both before and after correction for possible covariates, including patient metadata. However, we find that bacterial taxonomies are not significantly associated with clinical outcomes. Strikingly, in contrast, dozens of microbial proteins were significantly associated with poor patient outcomes and in particular, proteins that perform mitochondrial functions and iron-sulfur coordination. We further demonstrate associations between these microbial proteins and dysregulated host pathways in ESCA patients. Overall, these results suggest possible influences of bacteria on the development of ESCA and uncover new prognostic biomarkers based on microbial genes. In addition, this study provides a framework for the analysis of other human malignancies whose development may be driven by pathogens.

Larkinella humicola sp. nov., a gamma radiation-resistant bacterium isolated from soil

A Gram-negative, short rod-shaped, and pink-pigmented bacterial strain, designated MA1^T, was isolated from a soil sample from Gijang-gun, Busan in Republic of Korea. The 16S rRNA gene sequence analysis showed that strain MA1^T belonged to the genus Larkinella and was closely related to "Larkinella punicea" (97.5% similarity), Larkinella rosea 15J16-1T3A^T (96.5%), and Larkinella knui 15J6-3T6^T (96.2%). Polar lipid profile of strain MA1^T contained phosphatidylethanolamine, two unidentified aminolipids, and three unidentified lipids. Menaquinone-7 was the only quinone and the main fatty acids were C_16:1 ω5c (36.7%), iso-C_15:0 (30.0%), iso-C_17:0 3-OH (7.7%), and summed feature 3 (C_16:1 ω6c and/or C_16:1 ω7c and/or iso-C_15:0 2-OH) (7.3%). The genomic DNA G + C content was 52.3 mol% based on the whole-genome analysis. Strain MA1^T exhibited a relatively low level of ANI and in silico DDH values with "Larkinella punicea" (91.9 and 47.1%, respectively), Larkinella rosea (79.7 and 23.3%), and Larkinella knui (81.9 and 25.7%). Based on its phenotypic properties and phylogenetic distinctiveness, strain MA1^T should be classified in the genus Larkinella as a representative of a novel species, for which the name Larkinella humicola sp. nov. is proposed. The type strain is MA1^T (= KCTC 72629^T = NBRC 114191^T).