Propionibacterium acnes subsp. acnes subsp. nov. and Propionibacterium acnes subsp. elongatum subsp. nov. are described. These emanate from the three known phylotypes of P. acnes, designated types I, II and III. Electron microscopy confirmed the filamentous cell shape of type III, showing a striking difference from types I/II, which were short rods. Biochemical tests indicated that, in types I/II, either the pyruvate, l-pyrrolidonyl arylamidase or d-ribose 2 test was positive, whereas all of these were negative among type III strains. Matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) spectra, which profile mainly their ribosomal proteins, were different between these two groups. Surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) spectra of all phylotypes revealed a specific protein biomarker that was overexpressed in type III strains compared with types I/II only when grown aerobically. Reference strains had high whole-genome similarity between types I (>91 %) and II (>75 %), but a considerably lower level of 72 % similarity with type III. recA and gyrB sequence dendrograms confirmed the distant relatedness of type III, indicating the presence of two distinct centres of variation within the species P. acnes. On the other hand, cellular fatty acid profiles and 16S rRNA gene sequence relatedness (>99.3 %) circumscribed the species. Thus, we propose two subspecies, Propionibacterium acnes subsp. acnes subsp. nov. for types I/II and Propionibacterium acnes subsp. elongatum subsp. nov. for type III. The type strain of Propionibacterium acnes subsp. acnes is NCTC 737T ( = ATCC 6919T = JCM 6425T = DSM 1897T = CCUG 1794T), while the type strain of Propionibacterium acnes subsp. elongatum is K124T ( = NCTC 13655T = JCM 18919T).

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A high prevalence of virulence factors was demonstrated in both population types. SELDI-TOF-MS and MALDI-TOF-MS proved useful in distinguishing between different E. faecalis phenotypes and they may be useful technologies for elucidating the eco-distribution of E. faecalis in humans.

Propionibacterium acnes is one of the dominant commensals on the human skin and also an opportunistic pathogen in relation to acne, sarcoidosis, prostate cancer, and various infections. Recent investigations using housekeeping and virulence genes have revealed that the species consists of three major evolutionary clades (types I, II, and III). In order to investigate protein expression differences between these phylogroups, proteomic profiles of 21 strains of P. acnes were investigated. The proteins extracted from cells cultured under anaerobic and aerobic conditions were analysed using a SELDI-TOF mass spectrometer, high-resolution capillary gel electrophoresis, and LC-MS/ MS. The SELDI spectral profiles were visualised as a heat map and a dendrogram, which resulted in four proteomic groups. Strains belonging to type I were represented in the proteome Group A, while Group B contained type III strains. Groups C and D contained mixtures of types I and II. Each of these groups was not influenced by differences in culture conditions. Under anoxic growth conditions, a type IB strain yielded high expressions of some proteins, such as methylmalonyl-CoA epimerase and the Christie-Atkins-Munch-Petersen (CAMP) factor. The present study revealed good congruence between genomic and proteomic data suggesting that the microenvironment of each subtype may influence protein expression.

Surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS) has been applied in large numbers of oncological studies but the microbiological field has not been extensively explored to date. This paper describes the application of SELDI-TOF MS in concert with a multi-layer perceptron artificial neural network (ANN) with a back propagation algorithm for the identification of Neisseria gonorrhoeae. N. gonorrhoeae, the aetiological agent of gonorrhoea, is the second most common sexually transmitted disease in the UK and USA. Analysis of over 350 strains of N. gonorrhoeae and closely related species by SELDI-TOF MS facilitated the design of an ANN model and revealed 20 ion peak descriptors of positive, negative and secondary nature that were paramount for the identification of the pathogen. The model performed with over 96 % efficiency when based on these 20 ion peak descriptors and exhibited a sensitivity of 95 . 7 % and a specificity of 97 . 1 %, with an area under the curve value of 0 . 996. The technology has the potential to link several ANN models for a comprehensive rapid identification platform for clinically important pathogens.

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