DEEPOMICS FFPE, a deep neural network model, identifies DNA sequencing artifacts from formalin fixed paraffin embedded tissue with high accuracy.

Formalin-fixed, paraffin-embedded (FFPE) tissue specimens are routinely used in pathological diagnosis, but their large number of artifactual mutations complicate the evaluation of companion diagnostics and analysis of next-generation sequencing data. Identification of variants with low allele frequencies is challenging because existing FFPE filtering tools label all low-frequency variants as artifacts. To address this problem, we aimed to develop DEEPOMICS FFPE, an AI model that can classify a true variant from an artifact. Paired whole exome sequencing data from fresh frozen and FFPE samples from 24 tumors were obtained from public sources and used as training and validation sets at a ratio of 7:3. A deep neural network model with three hidden layers was trained with input features using outputs of the MuTect2 caller. Contributing features were identified using the SHapley Additive exPlanations algorithm and optimized based on training results. The performance of the final model (DEEPOMICS FFPE) was compared with those of existing models (MuTect filter, FFPolish, and SOBDetector) by using well-defined test datasets. We found 41 discriminating properties for FFPE artifacts. Optimization of property quantification improved the model performance. DEEPOMICS FFPE removed 99.6% of artifacts while maintaining 87.1% of true variants, with an F1-score of 88.3 in the entire dataset not used for training, which is significantly higher than those of existing tools. Its performance was maintained even for low-allele-fraction variants with a specificity of 0.995, suggesting that it can be used to identify subclonal variants. Different from existing methods, DEEPOMICS FFPE identified most of the sequencing artifacts in the FFPE samples while retaining more of true variants, including those of low allele frequencies. The newly developed tool DEEPOMICS FFPE may be useful in designing capture panels for personalized circulating tumor DNA assay and identifying candidate neoepitopes for personalized vaccine design. DEEPOMICS FFPE is freely available on the web ( http://deepomics.co.kr/ffpe ) for research.

Extreme furfural tolerance of a soil bacterium Enterobacter cloacae GGT036.

Detoxification process of cellular inhibitors including furfural is essential for production of bio-based chemicals from lignocellulosic biomass. Here we isolated an extreme furfural-tolerant bacterium Enterobacter cloacae GGT036 from soil sample collected in Mt. Gwanak, Republic of Korea. Among isolated bacteria, only E. cloacae GGT036 showed cell growth with 35 mM furfural under aerobic culture. Compared to the maximal half inhibitory concentration (IC50) of well-known industrial strains Escherichia coli (24.9 mM furfural) and Corynebacterium glutamicum (10 mM furfural) based on the cell density, IC50 of E. cloacae GGT036 (47.7 mM) was significantly higher after 24 h, compared to E. coli and C. glutamicum. Since bacterial cell growth was exponentially inhibited depending on linearly increased furfural concentrations in the medium, we concluded that E. cloacae GGT036 is an extreme furfural-tolerant bacterium. Recently, the complete genome sequence of E. cloacae GGT036 was announced and this could provide an insight for engineering of E. cloacae GGT036 itself or other industrially relevant bacteria.

Heat shock protein gene family of the Porphyra seriata and enhancement of heat stress tolerance by PsHSP70 in Chlamydomonas.

Heat shock proteins and molecular chaperones are key components contributing to survival in the abiotic stress response. Porphyra seriata grows on intertidal rocks exposed to dynamic environmental changes associated with the turning tides, including desiccation and heat stress. Analysis of the ESTs of P. seriata allows us to identify the nine HSP cDNAs, which are predicted to be PsHSP90, three PsHSP70, PsHSP40 and PsHSP20, and three 5'-truncated HSP cDNAs. RT-PCR results show that most of the PsHSP transcripts were detected under normal cell growth conditions as well as heat stress, with the exception of two cDNAs. In particular, PsHSP70b and PsHSP20 transcripts were upregulated by heat stress. When the putative mitochondrial PsHSP70b was introduced and overexpressed in Chlamydomonas, transformed Chlamydomonas evidenced higher rates of survival and growth than those of the wild type under heat stress conditions. Constitutive overexpression of the PsHSP70b gene increases the transcription of the HSF1 as well as the CrHSP20 and CrHSP70 gene. These results indicate that PsHSP70b is involved in tolerance to heat stress and the effects on transcription of the CrHSP20 and CrHSP70 genes.

IDENTIFICATION OF THE HIGH-TEMPERATURE RESPONSE GENES FROM PORPHYRA SERIATA (RHODOPHYTA) EXPRESSION SEQUENCE TAGS AND ENHANCEMENT OF HEAT TOLERANCE OF CHLAMYDOMONAS (CHLOROPHYTA) BY EXPRESSION OF THE PORPHYRA HTR2 GENE(1).

Temperature is one of the major environmental factors that affect the distribution, growth rate, and life cycle of intertidal organisms, including red algae. In an effort to identify the genes involved in the high-temperature tolerance of Porphyra, we generated 3,979 expression sequence tags (ESTs) from gametophyte thalli of P. seriata Kjellm. under normal growth conditions and high-temperature conditions. A comparison of the ESTs from two cDNA libraries allowed us to identify the high temperature response (HTR) genes, which are induced or up-regulated as the result of high-temperature treatment. Among the HTRs, HTR2 encodes for a small polypeptide consisting of 144 amino acids, which is a noble nuclear protein. Chlamydomonas expressing the Porphyra HTR2 gene shows higher survival and growth rates than the wild-type strain after high-temperature treatment. These results suggest that HTR2 may be relevant to the tolerance of high-temperature stress conditions, and this Porphyra EST data set will provide important genetic information for studies of the molecular basis of high-temperature tolerance in marine algae, as well as in Porphyra.