ABSTRACT
Halophilic bacteria are extremophiles that thrive in saline environment. Their ability to withstand such harsh conditions makes them an ideal choice for industrial applications such as lignocellulosic biomass degradation. In this study, a halophilic bacterium with the ability to produce extracellular cellulases and hemicellulases, designated as Nesterenkonia sp. CL21, was isolated from mangrove sediment in Tanjung Piai National Park, Malaysia. Thus far, studies on lignocellulolytic enzymes concerning bacterial species under this genus are limited. To gain a comprehensive understanding of its lignocellulose-degrading potential, the whole genome was sequenced using the Illumina NovaSeq 6000 platform. The genome of strain CL21 was assembled into 25 contigs with 3,744,449 bp and a 69.74% GC content and was predicted to contain 3,348 coding genes. Based on taxonomy analysis, strain CL21 shares 73.8 to 82.0% average nucleotide identity with its neighbouring species, below the 95% threshold, indicating its possible status as a distinct species in Nesterenkonia genus. Through in-depth genomic mining, a total of 81 carbohydrate-active enzymes were encoded. Among these, 24 encoded genes were identified to encompass diverse cellulases (GH3), xylanases (GH10, GH11, GH43, GH51, GH127 and CE4), mannanases (GH38 and GH106) and pectinases (PL1, PL9, and PL11). The production of lignocellulolytic enzymes was tested in the presence of several substrates. This study revealed that strain CL21 can produce a diverse array of enzymes which are active at different time points. By combining experimental data with genomic information, the ability of strain CL21 to produce lignocellulolytic enzymes has been elucidated, with potential applications in biorefinery industry.
ABSTRACT
The study of viral diversity is imperative in understanding sequence change and its implications for intervention strategies. The widely used alignment-dependent approaches to study viral diversity are limited in their utility as sequence dissimilarity increases, particularly when expanded to the genus or higher ranks of viral species lineage. Herein, we present an alignment-independent algorithm, implemented as a tool, UNIQmin, to determine the effective viral sequence diversity at any rank of the viral taxonomy lineage. This is done by performing an exhaustive search to generate the minimal set of sequences for a given viral non-redundant sequence dataset. The minimal set is comprised of the smallest possible number of unique sequences required to capture the diversity inherent in the complete set of overlapping k-mers encoded by all the unique sequences in the given dataset. Such dataset compression is possible through the removal of unique sequences, whose entire repertoire of overlapping k-mers can be represented by other sequences, thus rendering them redundant to the collective pool of sequence diversity. A significant reduction, namely ~44%, ~45%, and ~53%, was observed for all reported unique sequences of species Dengue virus, genus Flavivirus, and family Flaviviridae, respectively, while still capturing the entire repertoire of nonamer (9-mer) viral peptidome diversity present in the initial input dataset. The algorithm is scalable for big data as it was applied to ~2.2 million non-redundant sequences of all reported viruses. UNIQmin is open source and publicly available on GitHub. The concept of a minimal set is generic and, thus, potentially applicable to other pathogenic microorganisms of non-viral origin, such as bacteria.
