Thioalkalimicrobium cyclicum Sorokin et al. 2002 is a member of the family Piscirickettsiaceae in the order Thiotrichales. The γ-proteobacterium belongs to the colourless sulfur-oxidizing bacteria isolated from saline soda lakes with stable alkaline pH, such as Lake Mono (California) and Soap Lake (Washington State). Strain ALM 1(T) is characterized by its adaptation to life in the oxic/anoxic interface towards the less saline aerobic waters (mixolimnion) of the stable stratified alkaline salt lakes. Strain ALM 1(T) is the first representative of the genus Thioalkalimicrobium whose genome sequence has been deciphered and the fourth genome sequence of a type strain of the Piscirickettsiaceae to be published. The 1,932,455 bp long chromosome with its 1,684 protein-coding and 50 RNA genes was sequenced as part of the DOE Joint Genome Institute Community Sequencing Program (CSP) 2008.
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http://dx.doi.org/10.1186/s40793-016-0162-x | DOI Listing |
Clin Dysmorphol
December 2024
Department of Pediatric Genetics.
Introduction: Spondyloepimetaphyseal dysplasia with joint laxity type 1 (SEMD-JL1) is an extremely rare skeletal dysplasia belonging to a group of disorders called linkeropathies. It is characterized by skeletal and connective tissue abnormalities. Biallelic variants in genes encoding enzymes that synthesize the tetrasaccharide linker region of glycosaminoglycans lead to linkeropathies, which exhibit clinical and phenotypic features that overlap with each other.
View Article and Find Full Text PDFClin Dysmorphol
January 2025
Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India.
Introduction: Agrin, encoded by AGRN, plays a vital role in the acetylcholine receptor clustering pathway, and any defects in this pathway are known to cause congenital myasthenic syndrome (CMS) 8 in early childhood with variable fatigable muscle weakness. The most severe or lethal form of CMS manifests as a fetal akinesia deformation sequence (FADS). To date, only one family has been reported with an association of null variants in AGRN and a lethal FADS.
View Article and Find Full Text PDFAnal Chem
January 2025
State Key Laboratory of Integrated Optoelectronics, College of Electronics Science and Engineering, Jilin University, No. 2699 Qianjin Street, Changchun, Jilin 130012, P. R. China.
Hepatitis D virus (HDV) significantly influences the progression of liver diseases. Through clinical observations and database analyses, it has been established that patients coinfected with HDV and hepatitis B virus (HBV) experience accelerated progression toward cirrhosis, hepatocellular carcinoma (HCC), and liver failure compared to those infected solely with HBV. A higher viral load correlates with increased replicative activity, enhanced infectivity, and more severe disease manifestations.
View Article and Find Full Text PDFHeliyon
January 2025
Biotechnology Unit, ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, West Bengal, 700121, India.
Recent advances in genome editing tools and CRISPR-Cas technologies have enabled plant genome engineering reach new heights. The current regulatory exemptions for certain categories of genome edited products, such as those derived from SDN-1 and SDN-2, which are free of any transgene, have significantly accelerated genome editing research in a number of agricultural crop plants in different countries. Although CRISPR-Cas technology is becoming increasingly popular, it is still important to carefully consider a number of factors before planning and carrying conducting CRISPR-Cas studies.
View Article and Find Full Text PDFAnim Cells Syst (Seoul)
January 2025
Department of Genome Medicine and Science, Gachon University College of Medicine, Incheon, Republic of Korea.
Dynamic modeling of cellular states has emerged as a pivotal approach for understanding complex biological processes such as cell differentiation, disease progression, and tissue development. This review provides a comprehensive overview of current approaches for modeling cellular state dynamics, focusing on techniques ranging from dynamic or static biomolecular network models to deep learning models. We highlight how these approaches integrated with various omics data such as transcriptomics, and single-cell RNA sequencing could be used to capture and predict cellular behavior and transitions.
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