Monitoring the purity of industrial starter cultures using MALDI-TOF MS

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Exploration of matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) as a fast identification tool for beer spoilage bacteria

Beer spoilage induced by bacteria is a common problem in the brewing industry and has a great impact on the brewing economy. The present study aims to develop a quick, accurate and inexpensive method to detect and identify beer spoilage bacteria. To achieve this, an extensive database comprising about 6500 MALDI-TOF MS-profiles including more than 260 accurately identified contaminants and beer spoilage isolates was built. The 260 isolates represent all commonly encountered spoilage bacteria with a focus on lactobacilli, acetic acid bacteria and some anaerobes. The profiles revealed culture-independent species-specific biomarker peaks for all spoilage species, allowing straightforward identification of novel isolates. The final aim of the present study is to detect and identify spoilage bacteria in a sample with no or minimal culture steps

Introducing SPeDE : high-throughput dereplication and accurate determination of microbial diversity from matrix-assisted laser desorption-ionization time of flight mass spectrometry data

The isolation of microorganisms from microbial community samples often yields a large number of conspecific isolates. Increasing the diversity covered by an isolate collection entails the implementation of methods and protocols to minimize the number of redundant isolates. Matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry methods are ideally suited to this dereplication problem because of their low cost and high throughput. However, the available software tools are cumbersome and rely either on the prior development of reference databases or on global similarity analyses, which are inconvenient and offer low taxonomic resolution. We introduce SPeDE, a user-friendly spectral data analysis tool for the dereplication of MALDI-TOF mass spectra. Rather than relying on global similarity approaches to classify spectra, SPeDE determines the number of unique spectral features by a mix of global and local peak comparisons. This approach allows the identification of a set of nonredundant spectra linked to operational isolation units. We evaluated SPeDE on a data set of 5,228 spectra representing 167 bacterial strains belonging to 132 genera across six phyla and on a data set of 312 spectra of 78 strains measured before and after lyophilization and subculturing. SPeDE was able to dereplicate with high efficiency by identifying redundant spectra while retrieving reference spectra for all strains in a sample. SPeDE can identify distinguishing features between spectra, and its performance exceeds that of established methods in speed and precision. SPeDE is open source under the MIT license and is available from https://github.com/LM-UGent/SPeDE. IMPORTANCE Estimation of the operational isolation units present in a MALDI-TOF mass spectral data set involves an essential dereplication step to identify redundant spectra in a rapid manner and without sacrificing biological resolution. We describe SPeDE, a new algorithm which facilitates culture-dependent clinical or environmental studies. SPeDE enables the rapid analysis and dereplication of isolates, a critical feature when long-term storage of cultures is limited or not feasible. We show that SPeDE can efficiently identify sets of similar spectra at the level of the species or strain, exceeding the taxonomic resolution of other methods. The high-throughput capacity, speed, and low cost of MALDI-TOF mass spectrometry and SPeDE dereplication over traditional gene marker-based sequencing approaches should facilitate adoption of the culturomics approach to bacterial isolation campaigns

Burkholderia cepacia complex taxon K : where to split?

The objective of the present study was to provide an updated classification for Burkholderia cepacia complex (Bcc) taxon K isolates. A representative set of 39 taxon K isolates were analyzed through multilocus sequence typing (MLST) and phylogenomic analyses. MLST analysis revealed the presence of at least six clusters of sequence types (STs) within taxon K, two of which contain the type strains of Burkholderia contaminans (ST-102) and Burkholderia lata (ST-101), and four corresponding to the previously defined taxa Other Bcc groups C, G, H and M. This clustering was largely supported by a phylogenomic tree which revealed three main clades. Isolates of B. contaminans and of Other Bcc groups C, G, and H represented a first clade which generally shared average nucleotide identity (ANI) and average digital DNA-DNA hybridization (dDDH) values at or above the 95–96% ANI and 70% dDDH thresholds for species delineation. A second clade consisted of Other Bcc group M bacteria and of four B. lata isolates and was supported by average ANI and dDDH values of 97.2 and 76.1% within this clade and average ANI and dDDH values of 94.5 and 57.2% toward the remaining B. lata isolates (including the type strain), which represented a third clade. We therefore concluded that isolates known as Other Bcc groups C, G, and H should be classified as B. contaminans, and propose a novel species, Burkholderia aenigmatica sp. nov., to accommodate Other Bcc M and B. lata ST-98, ST-103, and ST-119 isolates. Optimized MALDI-TOF MS databases for the identification of clinical Burkholderia isolates may provide correct species-level identification for some of these bacteria but would identify most of them as B. cepacia complex. MLST facilitates species-level identification of many taxon K strains but some may require comparative genomics for accurate species-level assignment. Finally, the inclusion of Other Bcc groups C, G, and H into B. contaminans affects the phenotype of this species minimally and the proposal to classify Other Bcc group M and B. lata ST-98, ST-103, and ST-119 strains as a novel Burkholderia species is supported by a distinctive phenotype, i.e., growth at 42°C and lysine decarboxylase activity