China
Africa
Explore chapters and articles related to this topic
Functional Omics and Big Data Analysis in Microalgae
Published in Gokare A. Ravishankar, Ranga Rao Ambati, Handbook of Algal Technologies and Phytochemicals, 2019
Chetan Paliwal, Tonmoy Ghosh, Asha A. Nesamma, Pavan P. Jutur
Phylogenomics is the study of the evolutionary background of biological lineages based on the comparative analysis of genome-scale data, which simultaneously allows us to refer to the various biological queries at a scale not possible earlier. Large-scale data mining and analysis of sequential data sets offer a new insight into the development of new metabolic models, providing details of the molecular evolution of metabolic pathways (Misra et al. 2012). A phylogenomic study by Misra et al. (2012) deduced that lipid biosynthetic pathway related genes among Prasinophytes, Chlorophytes, Streptophytes, and Rhodophytes clustered based on exon-intron assembly, conserved motif arrangement and functionality. Also, genomes systematically mined from species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta identified 289 enzymes involved in lipid metabolic pathways, consequently building the Database of Enzymes of Microalgal Biofuel Feedstock (dEMBF). dEMBF is the first database developed for the enzymes involved and is responsible for lipid synthesis from 15 algal genomes, thereby building an informative platform for enzyme queries and analysis (http://bbprof.immt.res.in/embf, Misra et al. 2016). The Algae Gene Co-expression database (ALCOdb—http://alcodb.jp) is another database providing information on various microalgal gene co-expression at the interspecies level based on comparison and network analysis, facilitating microalgal molecular understanding and evolutionary approach (Aoki et al. 2016) among two model algae, C. reinhardtii, and Cyanidioschyzon merolae, highlighti ng the major gene family belonging to higher plants. Phylogenomics study of red algae highlights the evolution of the mevalonate (MVA) pathway for isoprenoid biosynthesis in Rhodophyta and offers in-depth understanding of the origin and evolution of various genes and metabolic pathways involved in 15 red algal species of Rhodophyta (Qiu et al. 2016).
Site-specialization of human oral Gemella species
Published in Journal of Oral Microbiology, 2023
Julian Torres-Morales, Jessica L. Mark Welch, Floyd E. Dewhirst, Gary G. Borisy
Microbial taxonomy is a challenging field that is increasingly being informed by whole-genome sequences. For the major Gemella species abundant in the healthy human microbiome – G. haemolysans, G. morbillorum, and G. sanguinis – existing species names are consonant with overall similarity at the nucleotide level (ANI), evolutionary relatedness estimated by phylogenomics, and gene content as shown in our pangenome. Thus, our analysis confirms that these species are well defined and well validated. By contrast, the genomes of G. sp. HMT−928, ‘G. massiliensis’, and G. sp. 6198 not only are highly similar to one another in gene content but also are nearly identical by ANI, with 99.5% to 99.7% pairwise identity. Therefore, these three genomes, although isolated from donors from three different geographic regions, represent the same species. The genome representing G. bergeri is close to this grouping in both gene content and ANI, with approximately 94.9% pairwise identity to each of the other three genomes and clustered tightly with them in the phylogenomic tree, and thus may be regarded as a sister taxon. Our findings are completely consistent with a recent ANI analysis of Gemella isolates in connection with virulence factors for opportunistic infections [35].
Interleukin-1β secretion induced by mucosa-associated gut commensal bacteria promotes intestinal barrier repair
Published in Gut Microbes, 2022
Wan-Jung H. Wu, Myunghoo Kim, Lin-Chun Chang, Adrien Assie, Fatima B. Saldana-Morales, Daniel F. Zegarra-Ruiz, Kendra Norwood, Buck S. Samuel, Gretchen E. Diehl
Fecal pellets from AVMN-treated mice were resuspended in PBS to 100 mg/ml and dilutions were plated on blood agar plates (Fisher) and cultured overnight at 37°C under normal or anaerobic conditions using BD GasPak (Fisher). For sequencing, genomic DNA was extracted with phenol chloroform, and DNA was sheared to 15kb using Covaris g-TUBE® devices, allowing for sizes 5 kb and larger. The library preparation was carried out using SMRTbell Template kit 1.0 Exo VII protocol and the sample was barcoded with PacBio Adaptor. Genome sequencing was performed using the Pacific Biosciences Sequel sequencing platform. Long reads were assembled de novo into two contigs (main chromosome and 1 plasmids) using Canu (v. 1.6).73 Gene prediction and annotation were carried out using the webservice PATRIC.74 Genomic visualization was performed using Circos v0.69–9.75 Genomic comparison was done using the PATRIC webservice and phylogenomic reconstructions were done using the GToTree pipeline and its associated dependencies.76–80 Sequencing reads and the genome assembly were submitted to NCBI under the bioproject PRJNA725420.
Limosilactobacillus reuteri DS0384 promotes intestinal epithelial maturation via the postbiotic effect in human intestinal organoids and infant mice
Published in Gut Microbes, 2022
Hana Lee, Kwang Bo Jung, Ohman Kwon, Ye Seul Son, Eunho Choi, Won Dong Yu, Naeun Son, Jun Hyoung Jeon, Hana Jo, Haneol Yang, Yeong Rak Son, Chan-Seok Yun, Hyun-Soo Cho, Sang Kyu Kim, Dae-Soo Kim, Doo-Sang Park, Mi-Young Son
Whole-genome sequencing of DS0384 was performed using PacBio RS II (Pacific Biosciences, Menlo Park, CA, USA) SMRT sequencing technology. A standard PacBio library with an average of 20-kb inserts was prepared and sequenced, yielding >286× average genome coverage. De novo assembly of the 81,092 subreads with 9,687 nucleotides on average (785,607,610 bp in total) was conducted using the hierarchical genome-assembly process pipeline of SMRT Analysis v2.3.0. To correct sequencing errors that can occur at both ends of a contig, the SMRT resequencing protocol was performed with an assembly in which the first half of the contig was switched with the second half. Protein-coding genes were predicted using Prodigal v.2.6.3. Ribosomal RNA and transfer RNA, and miscellaneous features were predicted using the CRISPR recognition tool Rfam v12.0.59 CRISPR loci. ANI values were calculated using an online ANI calculator.60 Phylogenomic analysis was performed using 92 bacterial core genes based on the up-to-date bacterial core gene tool (https://www.ezbiocloud.net/tools/ubcg) against 31 L. reuteri strains derived from the GenBank/EMBL/DDBJ database. Limosilactobacillus fermentum NBRC3959 was used as an outgroup. Representative genes were selected based on 1429 complete genome sequences, covering 28 phyla and providing a set of genes present in most of the genomes or highly conserved single-copy genes.61