Recent advancements in critical care: Part I.

Medical colleges are now developing or refurbishing their anaesthesia intensive care units. In most teaching colleges, the residency post includes working in the critical care unit (CCU). Critical care is a rapidly evolving and popular super-speciality for postgraduate students. In some hospitals, anaesthesiologists play a key role in the management of the CCU. As perioperative physicians, all anaesthesiologists should be aware of the recent advancements in diagnostic and monitoring gadgets and investigations in critical care so that they may manage perioperative events effectively. Haemodynamic monitoring gives us warning signs about the change in the internal milieu of the patient. Point-of-care ultrasonography helps in rapid differential diagnosis. Point-of-care diagnostics give us instant bed-side information on the condition of a patient. Biomarkers help in confirming diagnosis, in monitoring, treatment, and providing prognosis. Molecular diagnostics guide anaesthesiologists in providing specific treatment to a causative agent. This article touches upon all of these management strategies in critical care and attempts to put forth the recent advancements in this speciality.

Genome sequencing reveals molecular subgroups in oral epithelial dysplasia

Abstract This study aimed to analyze the molecular characteristics of oral epithelial dysplasia (OED), highlighting the pathways and variants of genes that are frequently mutated in oral squamous cell carcinoma (OSCC) and other cancers. Ten archival OED cases were retrieved for retrospective clinicopathological analysis and exome sequencing. Comparative genomic analysis was performed between high-grade dysplasia (HGD) and low-grade dysplasia (LGD), focusing on 57 well-known cancer genes, of which 10 were previously described as the most mutated in OSCC. HGD cases had significantly more variants; however, a similar mutational landscape to OSCC was observed in both groups. CASP8+FAT1/HRAS, TP53, and miscellaneous molecular signatures were also present. FAT1 is the gene that is most affected by pathogenic variants. Hierarchical divisive clustering showed division between the two groups: "HGD-like cluster" with 4HGD and 2LGD and "LGD-like cluster" with 4 LGD. MLL4 pathogenic variants were exclusively in the "LGD-like cluster". TP53 was affected in one case of HGD; however, its pathway was usually altered. We describe new insights into the genetic basis of epithelial malignant transformation by genomic analysis, highlighting those associated with FAT1 and TP53. Some LGDs presented a similar mutational landscape to HGD after cluster analysis. Perhaps molecular alterations have not yet been reflected in histomorphology. The relative risk of malignant transformation in this molecular subgroup should be addressed in future studies.

Revealing molecular architecture of FLT3 internal tandem duplication: Development and clinical validation of a web-based application to generate accurate nomenclature.

INTRODUCTION: FLT3 internal tandem duplicate (ITD) is associated with unfavorable prognosis of acute myeloid leukemia; targeted therapy improves clinical outcome. We propose that FLT3-ITD detected by next generation sequencing (NGS) should be reported with the same nomenclature pattern as single nucleotide variants so that the mutation can be better interpreted clinically. METHODS: A Python-based web application was developed to generate FLT3-ITD nomenclature as recommended by the Human Genome Variation Society (HGVS). Assembled FLT3-ITD sequences from 84 patients and 11 artificially created ITD sequences were used for the validation of this web-based application. Each sequence was inspected manually to confirm that the nomenclature was accurate. RESULTS: Accurate nomenclatures were generated for 113 of 114 sequencing results and 7 artificial sequences. One assembled sequence and four artificial sequences were not named accurately; warning statements were automatically generated to alert further inspection. Of the 105 unique FLT3-ITDs, the ITD lengths range from 18 to 300 bp. Depending whether the ITD involves intron or extends into exon 15, three patterns were recognized. Only 44 (42%) ITDs were pure duplications, and three types of variants were identified at the 5' of ITD. When ITD involves intronic sequence, the protein may comprise inserted amino acids encoded by the intron, due to disrupted RNA splicing. CONCLUSION: The web application generates accurate FLT3-ITD nomenclature from NGS results except in rare situations. The HGVS nomenclatures provide information on the molecular architecture of FLT3-ITDs and reveal details of complex insertions with partial duplications.

P2T2: Protein Panoramic annoTation Tool for the interpretation of protein coding genetic variants.

MOTIVATION: Genomic data are prevalent, leading to frequent encounters with uninterpreted variants or mutations with unknown mechanisms of effect. Researchers must manually aggregate data from multiple sources and across related proteins, mentally translating effects between the genome and proteome, to attempt to understand mechanisms. MATERIALS AND METHODS: P2T2 presents diverse data and annotation types in a unified protein-centric view, facilitating the interpretation of coding variants and hypothesis generation. Information from primary sequence, domain, motif, and structural levels are presented and also organized into the first Paralog Annotation Analysis across the human proteome. RESULTS: Our tool assists research efforts to interpret genomic variation by aggregating diverse, relevant, and proteome-wide information into a unified interactive web-based interface. Additionally, we provide a REST API enabling automated data queries, or repurposing data for other studies. CONCLUSION: The unified protein-centric interface presented in P2T2 will help researchers interpret novel variants identified through next-generation sequencing. Code and server link available at github.com/GenomicInterpretation/p2t2.

The complete mitochondrial genome of the oleaginous microalgae Ankistrodesmus falcatus strain UCP001 from the Peruvian Amazon.

Ankistrodesmus falcatus strain UCP001 is a native oleaginous microalgae isolated from the Peruvian Amazon basin. In this study we sequenced, de novo assembled, and functionally annotated the complete mitochondrial genome of the native oleaginous microalgae Ankistrodesmus falcatus strain UCP001 (Accesion number MT701044). This mitogenome is a typical circular double stranded DNA molecule of 41,048 bp in total length with G + C content of 37.4%. The mitogenome contains 49 genes, including 18 protein coding genes, 5 ribosomal (rRNA) genes and 26 transfer RNA (tRNA) genes. A phylogenetic analysis of 18 microalgae species indicated that Ankistrodesmus falcatus strain UCP001 was closely related to Ourococcus multisporus and Raphidocelis subcapitata. The complete mitochondrial genome sequence of Ankistrodesmus falcatus strain UCP001 enriches genomic resources of oleaginous native microalgae from the Peruvian Amazon for further basic and applied research.

Characterization of left-handed beta helix-domains, and identification and functional annotation of proteins containing such domains.

Only about 0.3% of the entries in UniProt database have manually curated annotation. Annotation at the molecular level often relies on low-throughput one-protein-at-a-time approach. Computational methods bridge this gap by assigning function based on sequence and/or fold similarity. Left-handed beta helix (LbH) consists of three repeating six-stranded beta-strands forming an 18-mer turn of the helix. Analysis of LbH-domains showed that variations are found in the number of residues in a beta-strand (5-7, 6 being the most common), number of turns (4-10) of the helix, insertions of one or more loops of variable length (0-36 residues), and the location of loop insertion. An 18-mer HMM profile was created which identifies LbH-domain containing proteins using sequence as the only input; the number of false positives is zero when proteins tested were those with known 3D structures. 136 474 entries of TrEMBL database were found to contain LbH-domain. Rules developed by analyzing LbH-domain containing acyltransferases, gamma-class carbonic anhydrases, and nucleotidyltransferases have led to the annotation of 17 389 TrEMBL entries which currently have no functional tag.

Dataset of de novo assembly and functional annotation of the transcriptome during germination and initial growth of seedlings of Myrciaria Dubia "camu-camu".

Myrciaria dubia "camu-camu" is a native shrub of the Amazon that is commonly found in areas that are flooded for three to four months during the annual hydrological cycle. This plant species is exceptional for its capacity to biosynthesize and accumulate important quantities of a variety of health-promoting phytochemicals, especially vitamin C [1], yet few genomic resources are available [2]. Here we provide the dataset of a de novo assembly and functional annotation of the transcriptome from a pool of samples obtained from seeds during the germination process and seedlings during the initial growth (until one month after germination). Total RNA/mRNA was purified from different types of plant materials (i.e., imbibited seeds, germinated seeds, and seedlings of one, two, three, and four weeks old), pooled in equimolar ratio to generate the cDNA library and RNA paired-end sequencing was conducted on an Illumina HiSeq™2500 platform. The transcriptome was de novo assembled using Trinity v2.9.1 and SuperTranscripts v2.9.1. A total of 21,161 transcripts were assembled ranging in size from 500 to 10,001 bp with a N50 value of 1,485 bp. Completeness of the assembly dataset was assessed using the Benchmarking Universal Single-Copy Orthologs (BUSCO) software v2/v3. Finally, the assembled transcripts were functionally annotated using TransDecoder v3.0.1 and the web-based platforms Kyoto Encyclopedia of Genes and Genomes (KEGG) Automatic Annotation Server (KAAS), and FunctionAnnotator. The raw reads were deposited into NCBI and are accessible via BioProject accession number PRJNA615000 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA615000) and Sequence Read Archive (SRA) with accession number SRX7990430 (https://www.ncbi.nlm.nih.gov/sra/SRX7990430). Additionally, transcriptome shotgun assembly sequences and functional annotations are available via Discover Mendeley Data (https://data.mendeley.com/datasets/2csj3h29fr/1).

Gene and Protein Network Analysis of AmpC ß Lactamase.

AmpC ß-lactamase is a cephalosporinase, which exhibits resistance against all existing ß-lactam antibiotics except carbapenems. Their occurrence in many bacterial pathogens poses a threat to public health and is a growing concern in the medical world. The ampC gene is highly inducible in the presence of ß-lactam antibiotics and can be expressed in high levels due to mutation. This inducible expression is regulated by several functional genes. Several studies on functional relationship of these genes and its resistance mechanisms are carried out but it still lacks comprehensible evidences. Thus, in our current study, we used computational gene networks to analyze ampC gene. Based on its interaction type, co-expression, Gene Ontology, and text mining, a functional interaction network is constructed. Around 247 functional genes in 15 different bacterial genus have a functional association with ampC gene. It is predicted that 19.8% ampD, 13.3% frdD, 8.5% gcvA, 2.4% ampR, and 55.7% of other functional partners are associated with ampC gene. Our present study provides a glimpse about the functional gene network of ampC gene and also provides the integrated evidence for ampC gene in regulating the ß-lactamase production and its role in antibiotic resistance.

AnsNGS: An Annotation System to Sequence Variations of Next Generation Sequencing Data for Disease-Related Phenotypes.

OBJECTIVES: Next-generation sequencing (NGS) data in the identification of disease-causing genes provides a promising opportunity in the diagnosis of disease. Beyond the previous efforts for NGS data alignment, variant detection, and visualization, developing a comprehensive annotation system supported by multiple layers of disease phenotype-related databases is essential for deciphering the human genome. To satisfy the impending need to decipher the human genome, it is essential to develop a comprehensive annotation system supported by multiple layers of disease phenotype-related databases. METHODS: AnsNGS (Annotation system of sequence variations for next-generation sequencing data) is a tool for contextualizing variants related to diseases and examining their functional consequences. The AnsNGS integrates a variety of annotation databases to attain multiple levels of annotation. RESULTS: The AnsNGS assigns biological functions to variants, and provides gene (or disease)-centric queries for finding disease-causing variants. The AnsNGS also connects those genes harbouring variants and the corresponding expression probes for downstream analysis using expression microarrays. Here, we demonstrate its ability to identify disease-related variants in the human genome. CONCLUSIONS: The AnsNGS can give a key insight into which of these variants is already known to be involved in a disease-related phenotype or located in or near a known regulatory site. The AnsNGS is available free of charge to academic users and can be obtained from http://snubi.org/software/AnsNGS/.

AnsNGS: An Annotation System to Sequence Variations of Next Generation Sequencing Data for Disease-Related Phenotypes / 대한의료정보학회지

OBJECTIVES: Next-generation sequencing (NGS) data in the identification of disease-causing genes provides a promising opportunity in the diagnosis of disease. Beyond the previous efforts for NGS data alignment, variant detection, and visualization, developing a comprehensive annotation system supported by multiple layers of disease phenotype-related databases is essential for deciphering the human genome. To satisfy the impending need to decipher the human genome, it is essential to develop a comprehensive annotation system supported by multiple layers of disease phenotype-related databases. METHODS: AnsNGS (Annotation system of sequence variations for next-generation sequencing data) is a tool for contextualizing variants related to diseases and examining their functional consequences. The AnsNGS integrates a variety of annotation databases to attain multiple levels of annotation. RESULTS: The AnsNGS assigns biological functions to variants, and provides gene (or disease)-centric queries for finding disease-causing variants. The AnsNGS also connects those genes harbouring variants and the corresponding expression probes for downstream analysis using expression microarrays. Here, we demonstrate its ability to identify disease-related variants in the human genome. CONCLUSIONS: The AnsNGS can give a key insight into which of these variants is already known to be involved in a disease-related phenotype or located in or near a known regulatory site. The AnsNGS is available free of charge to academic users and can be obtained from http://snubi.org/software/AnsNGS/.