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An Overview of Parasite Diversity
Published in Eric S. Loker, Bruce V. Hofkin, Parasitology, 2023
Eric S. Loker, Bruce V. Hofkin
Lest we draw an erroneous conclusion that parasites might always be expected to have genomes of reduced size compared to free-living relatives, consider that the parasitic lifestyle offers many challenges to overcome, requiring distinctive genetic innovations. These include the need to locate a host, to penetrate and navigate through the host’s body and to overcome host defenses and acquire nutrition. Many parasites have complex life cycles involving in some cases residence in multiple, often quite different host species living in distinct environments. Consequently, parasitism is not necessarily a one-way trip to genome reduction and reduced synthetic or biochemical versatility but can lead to impressive expansions of particular gene families. For instance, it is intriguing that not all microsporidian genomes have gone the reductive route of E. cuniculi. Some like Ordospora colligata, a parasite of water fleas (Daphnia sp.), has a genome of 24 Mb, almost ten times the size of the E. cuniculi genome. Another example of the extent to which genome properties vary is provided by an overview of some prominent apicomplexan genomes in Figure 2.31. Central to this discussion are orthologous genes, or orthologs, from different species that originate from a common ancestral gene found in the ancestor of those species.
Introduction to lactic acidemias
Published in William L. Nyhan, Georg F. Hoffmann, Aida I. Al-Aqeel, Bruce A. Barshop, Atlas of Inherited Metabolic Diseases, 2020
William L. Nyhan, Georg F. Hoffmann, Aida I. Al-Aqeel, Bruce A. Barshop
Molecular chaperones are required for the assembly of the catalytic F1 component of the mitochondrial ATP synthase, and probably for many other proteins involved in mitochondrial function. Those for F1 have been well studied in yeast and mutations in Saccharomyces are known. The human genes for orthologs are known. Their study may reveal novel mechanisms of mitochondrial disease.
Assessing the Microbiome—Current and Future Technologies and Applications
Published in David Perlmutter, The Microbiome and the Brain, 2019
Thomas Gurry, Shrish Budree, Alim Ladha, Bharat Ramakrishna, Zain Kassam
As the field of microbiome sequencing progresses, investigators are striving to unearth the mechanisms underlying host–microbiome interactions. This requires researchers to study the function of a host’s microbiome and not just its identity. Using both 16S and, more reliably, shotgun metagenomics, researchers can now determine the functional capacity of a microbial community. This type of analysis is facilitated by a computational software package like PICRUSt. Metagenomic data can be mapped against a reference database called the Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) to determine representative metabolic pathways present in a given sample. With 16S data, OTUs must be mapped to phylogenetic trees and reference databases containing information on their broader genetic code, a method which is only moderately reliable (Langille et al. 2013). Therefore, shotgun metagenomics provides a significantly more reliable method for determining functional profiles of the microbiome.
The ancestral stringent response potentiator, DksA has been adapted throughout Salmonella evolution to orchestrate the expression of metabolic, motility, and virulence pathways
Published in Gut Microbes, 2022
Helit Cohen, Boaz Adani, Emiliano Cohen, Bar Piscon, Shalhevet Azriel, Prerak Desai, Heike Bähre, Michael McClelland, Galia Rahav, Ohad Gal-Mor
To compare DEGs between S. Typhimurium, S. bongori, and E. coli, we created a dataset consisting of 2,896 orthologous core genes present in all three species (Table S2). Annotated genomes for S. bongori serovar 48z41 – strain RKS3044 (accession number NZ_CP006692), S. Typhimurium strain SL1344 (accession number NC_016810) and E. coli strain BW25113 (accession number NZ_CP009273) were downloaded from PATRIC.77 Proteinortho78 was used to determine orthology using amino acid fasta files. Phyletic patterns created using the orthology mapping were used to estimate core genomes between three species. Unless otherwise specified, all orthologous genes were named as in S. Typhimurium SL1344 to avoid confusion over different annotations of the same gene. Differentially expressed genes (adjusted P-value <0.05 and fold change ≥2) of the complete transcriptomes were analyzed by KEGG Mapper,79 using the corresponding organism databases. For genes involved in pathways of interest, the normalized reads were plotted in heatmaps using the R pheatmap package (Version 1.0.12).
The Mucosally-Adherent Rectal Microbiota Contains Features Unique to Alcohol-Related Cirrhosis
Published in Gut Microbes, 2021
Ting-Chin David Shen, Scott G. Daniel, Shivali Patel, Emily Kaplan, Lillian Phung, Kaylin Lemelle-Thomas, Lillian Chau, Lindsay Herman, Calvin Trisolini, Aimee Stonelake, Emily Toal, Vandana Khungar, Kyle Bittinger, K. Rajender Reddy, Gary D. Wu
Shotgun metagenomic analysis of rectal swab and stool samples are performed by the Sequencing and Analytical Center of the PennCHOP Microbiome Program to determine all of the genetic material available within the given samples. To do this, DNA are purified from each sample using the MoBio PowerSoil kit. Libraries for DNA sequencing are prepared using the TruSeq method, and sequences are acquired using the Illumina HiSeq method. Shotgun metagenomic data are analyzed using Sunbeam, a user-extendable bioinformatics pipeline that we developed for this purpose.50 Quality control steps are performed by the default workflows in Sunbeam, which are optimized to remove host-derived sequences and reads of low sequence complexity. The abundance of bacteria are estimated using Kraken.51 Reads are mapped to the KEGG database52 using Diamond53 to estimate the abundance of bacterial gene orthologs. Sample similarity are assessed by Bray-Curtis and Jaccard distances, and community-level differences between sample groups are assessed using the PERMANOVA test. Linear models were used to detect differences in logit-transformed gene and taxon abundance between sample groups. P-values from multiple testing procedures were corrected to control for a false discovery rate of 0.05. Continuous variable statistics are computed by Student’s t-tests. Categorical variable statistics are computed by Fisher’s exact test.
Probiotics maintain the intestinal microbiome homeostasis of the sailors during a long sea voyage
Published in Gut Microbes, 2020
Jiachao Zhang, Jinshan Zhao, Hao Jin, Ruirui Lv, Huiwen Shi, Guozhong De, Bo Yang, Zhihong Sun, Heping Zhang
To investigate the observed differences in the functional profiles of the intestinal microbiota during the long sea voyage, high-quality reads from all samples were assembled and annotated for protein-coding genes. Based on the results, a collective, non-redundant intestinal microbiota gene catalog was created. Next, for each sample, the reads were mapped to the collective gene catalog to reconstruct sample-specific gene profiles, and metabolic pathways were also generated with the Kyoto Encyclopedia of Genes and Genomes Orthology database (Tables S7 and S8). PCoA was performed based on the Bray–Curtis distances of the intestinal microbial functional gene profiles (Figure S3), and the specific changes in the microbial metabolic pathway were represented by a decreased toluene degradation ability and ubiquinol and glycogen synthesis ability (Table 1). Additionally, a significant shift from the intestinal microbial carbohydrate-active enzyme (CAZy) gene profile (Table S9) based on the Bray–Curtis distances (Figure 3(a)) and a sharp decline in the alpha diversity of microbial CAZy genes (Figure 3(b)) were observed at the end of the voyage in the placebo group, which were represented by a decrease in the relative abundance of the gene families glycoside hydrolases (GH), glycosyltransferases (GT) and polysaccharide lyases (PL) (Figure 3(c)). These results indicated that the long sea voyage not only disordered the balance of the intestinal microbiota of sailors but also reduced the diversity of functional features of intestinal microbiota.