Robustness of a FT-IR ANN-based technique in the identification of new species of the Burkholderia cepacia complex

A. BOSCH; P. MARTINA; J. DEGROSSI; A. MIÑÁN; V, FANESI; L. GALANTERNIK; P. MONTANARO; C. VAY; M. FRANCO; J. SHMITT; D. NAUMANN; O. M. YANTORNO

San José dos Campos. Sao Paulo. Brasil

Workshop; Spec 2008. Shedding Light on Disease: Optical Diagnosis for the New Millennium; 2008

Universidad del Valle de Paraiba

Members of the genus Burkholderia are versatile organisms that occupy a surprisingly wide range of ecological niches. They are routinely isolated from the natural environment, where they have diverse beneficial properties. However, all Burkholderia can also be opportunistic pathogens in humans. Indeed, bacteria of the Burkholderia cepacia Complex (BCC) are responsible for devastating lung infections in cystic fibrosis (CF) patients and various infections in inmunocompromised non-CF patients. BCC bacteria used to be mainly patient-to-patient transmitted. Nevertheless, due to the implementation of strict infection control practices in hospitals in the last years, this source of infection was reduced. Indeed, recent reviews, describing the current status of BCC in CF infections, has clearly demonstrated that the environment and industries represent the reservoirs of new pathogenic strains for both CF and non-CF patients (1, 2). Therefore, the epidemiology of BCC has been changing in the last years.The isolation and reliable identification of BCC bacteria is still a serious problem in clinical microbiology laboratories, it is very limited in environmental samples, and still not implemented in industrial settings. Moreover, the taxonomic complexity of BCC and its dramatic evolution has contributed to unreliable identifications. Even though 9 distinct species of closely related bacteria (genomovars) are known to comprise what is referred to as the BCC, recently, genetic methods such as recA gene sequence analysis and multilocus sequence typing (MLST), have allowed the inclusion of 1 additional species to the complex and the designation of 5 novel BCC species and one group of bacteria known as Taxon K, which comprises at least two novel species (B. vanimaris and B. lata) (2, 3). The aim of present work is to show the robustness of ANNs-FTIR spectroscopy-based technology to accurate and rapidly identify BCC environmental isolates and clinical isolates belonging to both CF and non-CF patients at the species level. After 3 years of working (2004-2007) in collaboration with different CF health care centres in Argentina, we proved the high reliability and strong potential of ANNs-FT-IR spectroscopy-based methodology for the rapid identification of gram-negative rods suitable for routine microbiology diagnosis in CF patients (5). In that research we used recA-RFLP and species-specific-PCR identification techniques which were the gold standards for identification of BCC species at that time. However, throughout 2007 and 2008, applying recA sequencing analysis identification technique, we found that among the isolates that were previously identified as B. cenocepacia (genomovar III), there were few putative B.cenocepaica strains, and most of them belonged to the novel Taxon K of BCC. Therefore, we updated our multivariate identification system which has showed robustness in discriminating and identifying bacteria belonging to Taxon K from the rest of the BCC species. We could also establish that the updated ANNs-FTIR based model developed is able to identify clinical non-CF isolates. On the other hand, we have found that most of the phenotypic characteristics (such us colony size, FTIR spectra, etc) of BCC clinical and environmental isolates with the same genomic identity at the species level are significantly different. Therefore, the ANNs-FTIR based system developed for clinical isolates was not accurate for the identification of environmental isolates; consequently, a different multivariate identification system is being developed for the discrimination and identification of environmental samples. The updated ANNs-based FTIR identification model developed is currently serving in the microbiology diagnosis of CF patients in some CF centres in Argentina, and it is actually contributing, together with other cooperative techniques, to determine therapeutic options and infection control measures. Indeed, the construction of a new spectral database and the development of a reliable multivariate identification system for environmental isolates will help to perform a systematic study focusing to find the main source of BCC infections. <!-- /* Font Definitions */ @font-face {font-family:Dutch801BT-Roman; panose-1:0 0 0 0 0 0 0 0 0 0; mso-font-charset:0; mso-generic-font-family:roman; mso-font-format:other; mso-font-pitch:auto; mso-font-signature:3 0 0 0 1 0;} /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0cm; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman";} @page Section1 {size:612.0pt 792.0pt; margin:70.85pt 3.0cm 70.85pt 3.0cm; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} -->