What can genome analysis offer for bacteria?

Author(s):  
Markus Göker

Abstract This book chapter is organized as follows: (i) the main approaches to the philosophy of taxonomic classification are recapitulated; (ii) the paradigm of polyphasic taxonomy is discussed in this context; (iii) the causes of conflict between previous classifications and genome-scale analyses are investigated, using examples from recent phylum-wide studies, with a discussion of how markers used in polyphasic taxonomy can be replaced by genome-derived ones; and (iv) the challenges in assigning taxonomic ranks using genome-scale or other data are revisited. The conclusion assesses the chances, or lack thereof, of reconciling taxonomic classifications. Phenetic and phylogenetic thinking still compete with each other on the classification of bacteria, with potentially conflicting and confusing results. Some causes of problematic taxonomic classifications are independent of the type and number of characters that can be used and can only be mitigated if, for example, taxon sampling and branch support are more appropriately taken into account. It may be possible to devise objective criteria for separating bacterial species, but the currently dominating approaches for microbial species delineation may be inadequate. It is even harder to delineate higher taxa; in contrast to claims in the literature, it may prove to be impossible to objectively assign taxonomic ranks above species level.

1986 ◽  
Vol 28 (5) ◽  
pp. 770-776 ◽  
Author(s):  
Kevin B. Jensen ◽  
Douglas R. Dewey ◽  
Kay H. Asay

Elymus alatavicus (Drob.) A. Love and E. batalinii (Krasn.) A. Love were studied to determine (i) meiotic behaviour, (ii) the mode of reproduction, (iii) the relationship between the two species, (iv) genomic constitutions, and (v) the most logical taxonomic classification of both species. A series of F1 hybrids between E. alatavicus, E. batalinii, and six "analyzer" species were developed. Chromosome pairing was studied at metaphase I to identify genomic similarities or differences. The results showed that E. alatavicus and E. batalinii are caespitose, self-fertile allohexaploids (2n = 42) with the same genomic formula SSYYXX. The F1 hybrids between E. alatavicus and E. batalinii had complete pairing (21 bivalents) at metaphase I in 7% of the cells and almost complete pairing in the remaining cells. High chromosome pairing and partial fertility (4 seeds/plant) in the F1 hybrids shows that the two species are closely related. Hybrids were obtained between E. alatavicus or E. batalinii and the following "analyzer" species with known genomic formulas: Pseudoroegneria spicata (Pursh) A. Love, 2n = 14, SS; P. cognata (Hack.) A. Love, 2n = 14, SS; E. lanceolatus (Scribn. &Smith) Gould, 2n = 28, SSHH; E. trachycaulus1 (Link) Gould ex Shinners, 2n = 28, SSHH; E. mutabilis (Drob.) Tzvelev, 2n = 28, SSHH; and E. drobovii (Nevski) Tzvelev, 2n = 42, SSHHYY. Chromosome pairing in this series of hybrids demonstrated that E. alatavicus and E. batalinii contain an S and probably a Y genome plus an unknown genome, X, that may have been derived from Psathryostachys huashanica Keng or from Agropyron. Elymus alatavicus and E. batalinii are correctly classified in the genus Elymus.Key words: cytotaxonomy, Agropyron, meiosis, chromosome.


2021 ◽  
Author(s):  
Andrew E. Schriefer ◽  
Brajendra Kumar ◽  
Avihai Zolty ◽  
Preetam R ◽  
Adam Didier ◽  
...  

The M-CAMP™ (Microbiome Computational Analysis for Multiomic Profiling) Cloud Platform was designed to provide users with an easy-to-use web interface to access best in class microbiome analysis tools. This interface allows bench scientists to conduct bioinformatic analysis on their samples and then download publication-ready graphics and reports. The core pipeline of the platform is the 16S-seq taxonomic classification algorithm which provides species-level classification of Illumina 16s sequencing. This algorithm uses a novel approach combining alignment and kmer based taxonomic classification methodologies to produce a highly accurate and comprehensive profile. Additionally, a comprehensive proprietary database combining reference sequences from multiple sources was curated and contains 18056 unique V3-V4 sequences covering 11527 species. The M-CAMPTM 16S taxonomic classification algorithm was validated on 52 sequencing samples from both public and in-house standard sample mixtures with known fractions. Compared to current popular public classification algorithms, our classification algorithm provides the most accurate species-level classification of 16S rRNA sequencing data.


Author(s):  
Frederick M. Cohan

Abstract This book chapter argues that bacterial systematists of the mid-20th century fortuitously created a species-level systematics that actually fits an important universal theory of speciation by discussing taxonomy would allow us to infer the important characteristics of any unknown organism once we classify it to species. It turns out, unexpectedly, that bacterial species taxa share a species-like property with the species taxa of zoology and botany. While recombination within species taxa of all these groups fails to prevent diversification within species, recombination nevertheless appears to act universally as a force of cohesion within species taxa. That is, recurrent recombination within species limits neutral sequence divergence within species taxa of plants, animals, and bacteria; recombination also allows a sharing of generally adaptive genes across a species range. The 95% ANI criterion that demarcates the traditionally defined species taxa of bacteria fortuitously also yields groups of bacteria that are subject to the species-like property of cohesion, where recombination prevents neutral sequence divergence among ecotypes within a species. Use of the ANI criterion, then, not only provides an easily used algorithm for demarcating bacterial species; it also places bacterial demarcation on the same theory-based foundation as the species taxonomy of animals and plants.


Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jack Jansma ◽  
Sahar El Aidy

AbstractThe human gut harbors an enormous number of symbiotic microbes, which is vital for human health. However, interactions within the complex microbiota community and between the microbiota and its host are challenging to elucidate, limiting development in the treatment for a variety of diseases associated with microbiota dysbiosis. Using in silico simulation methods based on flux balance analysis, those interactions can be better investigated. Flux balance analysis uses an annotated genome-scale reconstruction of a metabolic network to determine the distribution of metabolic fluxes that represent the complete metabolism of a bacterium in a certain metabolic environment such as the gut. Simulation of a set of bacterial species in a shared metabolic environment can enable the study of the effect of numerous perturbations, such as dietary changes or addition of a probiotic species in a personalized manner. This review aims to introduce to experimental biologists the possible applications of flux balance analysis in the host-microbiota interaction field and discusses its potential use to improve human health.


2020 ◽  
Vol 11 ◽  
Author(s):  
Shu-Ting Cho ◽  
Hung-Jui Kung ◽  
Weijie Huang ◽  
Saskia A. Hogenhout ◽  
Chih-Horng Kuo

Geoderma ◽  
2003 ◽  
Vol 115 (1-2) ◽  
pp. 31-44 ◽  
Author(s):  
Min Zhang ◽  
Li Ma ◽  
Wenqing Li ◽  
Baocheng Chen ◽  
Jiwen Jia

BMC Genomics ◽  
2011 ◽  
Vol 12 (Suppl 4) ◽  
pp. S11 ◽  
Author(s):  
Anderson R Santos ◽  
Marcos A Santos ◽  
Jan Baumbach ◽  
John A McCulloch ◽  
Guilherme C Oliveira ◽  
...  

Genetics ◽  
2020 ◽  
Vol 217 (2) ◽  
Author(s):  
Verónica Mixão ◽  
Ester Saus ◽  
Teun Boekhout ◽  
Toni Gabaldón

Abstract Candida albicans is the most commonly reported species causing candidiasis. The taxonomic classification of C. albicans and related lineages is controversial, with Candida africana (syn. C. albicans var. africana) and Candida stellatoidea (syn. C. albicans var. stellatoidea) being considered different species or C. albicans varieties depending on the authors. Moreover, recent genomic analyses have suggested a shared hybrid origin of C. albicans and C. africana, but the potential parental lineages remain unidentified. Although the genomes of C. albicans and C. africana have been extensively studied, the genome of C. stellatoidea has not been sequenced so far. In order to get a better understanding of the evolution of the C. albicans clade, and to assess whether C. stellatoidea could represent one of the unknown C. albicans parental lineages, we sequenced C. stellatoidea type strain (CBS 1905). This genome was compared to that of C. albicans and of the closely related lineage C. africana. Our results show that, similarly to C. africana, C. stellatoidea descends from the same hybrid ancestor as other C. albicans strains and that it has undergone a parallel massive loss of heterozygosity.


2021 ◽  
Author(s):  
Rajan Saha Raju ◽  
Abdullah Al Nahid ◽  
Preonath Shuvo ◽  
Rashedul Islam

AbstractTaxonomic classification of viruses is a multi-class hierarchical classification problem, as taxonomic ranks (e.g., order, family and genus) of viruses are hierarchically structured and have multiple classes in each rank. Classification of biological sequences which are hierarchically structured with multiple classes is challenging. Here we developed a machine learning architecture, VirusTaxo, using a multi-class hierarchical classification by k-mer enrichment. VirusTaxo classifies DNA and RNA viruses to their taxonomic ranks using genome sequence. To assign taxonomic ranks, VirusTaxo extracts k-mers from genome sequence and creates bag-of-k-mers for each class in a rank. VirusTaxo uses a top-down hierarchical classification approach and accurately assigns the order, family and genus of a virus from the genome sequence. The average accuracies of VirusTaxo for DNA viruses are 99% (order), 98% (family) and 95% (genus) and for RNA viruses 97% (order), 96% (family) and 82% (genus). VirusTaxo can be used to detect taxonomy of novel viruses using full length genome or contig sequences.AvailabilityOnline version of VirusTaxo is available at https://omics-lab.com/virustaxo/.


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