Defining pathogenic bacterial species in the genomic era
Authors: Didier Raoult
Kalliopi Georgiades
Journal: Frontiers in Microbiology (2010)
Discipline: MICROBIOLOGY
Keywords: allopatry; evolution; gene loss; pathogens; speciation
Affiliations: Faculté de Médecine et de Pharmacie, Unité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes, CNRS-IRD, UMR 6236, IFR48 Marseille, France.

Abstract:  Actual definitions of bacterial species are limited due to the current criteria of definition and the use of restrictive genetic tools. The 16S ribosomal RNA sequence, for example, has been widely used as a marker for phylogenetic analyses; however, its use often leads to misleading species definitions. According to the first genetic studies, removing a certain number of genes from pathogenic bacteria removes their capacity to infect hosts. However, more recent studies have demonstrated that the specialization of bacteria in eukaryotic cells is associated with massive gene loss, especially for allopatric endosymbionts that have been isolated for a long time in an intracellular niche. Indeed, sympatric free-living bacteria often have bigger genomes and exhibit greater resistance and plasticity and constitute species complexes rather than true species. Specialists, such as pathogenic bacteria, escape these bacterial complexes and colonize a niche, thereby gaining a species name. Their specialization allows them to become allopatric, and their gene losses eventually favor reductive genome evolution. A pathogenic species is characterized by a gene repertoire that is defined not only by genes that are present but also by those that are lacking. It is likely that current bacterial pathogens will disappear soon and be replaced by new ones that will emerge from bacterial complexes that are already in contact with humans. 

Retracted: No

PubPeer comments:
 The authors developed a method (Proposition 1) to project a so-called q-ROFN to an IFN. However, according to the numerical examples illustrated in Table 1, this method is numerically unstable and hence the methods based on such a projection method are also unstable. For example, let $$A= (0.5, 0.5)$$ Since $A$ is considered as a 1-ROFN, it is projected to itself as $$hat{A}= (0.5, 0.5)$$ Let $$B=(0.50001, 0.5)$$ It is considered as a 2-ROFN since $$0.50001+ 0.5 1 quad text{and}quad 0.50001^2 + 0.5^2 1$$ According to eq.(6), it is projected to $$hat{B} = (0.353562, 0.353552)$$ This means that a slight perturbation in the original data would lead to a significant change in the projected data. Such a phenomenon is not desired particularly when optimization problems are involved as in this paper. ![file] ![file] , 
 The notions of consistency defined in this paper for q-ROFPRs also make no sense. For example, according Definition 8, the consistency is characterized by a vector of intervals. However, consider $q=1$, the case of intuitionistic fuzzy relations. The diagonal elements are $$(mu_{ii},  u_{ii}) =(0.5, 0.5)$$ Then, according to eq.(10) in Definition 8, $$1= mu_{ii} -  u_{ii} +( mu_{ii}^q +  u_{ii}^q )^{1 q} = w_i^l -w_j^u +1$$ This implies that $$w_i^l=w_j^u,quad i=1, 2,ldots, n$$ As a consequence, the results based on such a notion are not sound. ![file] ,