Genome Sequence of Rapid Beer-Spoiling Isolate Lactobacillus brevis BSO 464.

The genome of brewery-isolate Lactobacillus brevis BSO 464 was sequenced and assembly produced a chromosome and eight plasmids. This bacterium tolerates dissolved CO2/pressure and can rapidly spoil packaged beer. This genome is useful for analyzing the genetics associated with beer spoilage by lactic acid bacteria.

Role of plasmids in Lactobacillus brevis BSO 464 hop tolerance and beer spoilage.

Specific isolates of lactic acid bacteria (LAB) can grow in the harsh beer environment, thus posing a threat to brew quality and the economic success of breweries worldwide. Plasmid-localized genes, such as horA, horC, and hitA, have been suggested to confer hop tolerance, a trait required for LAB survival in beer. The presence and expression of these genes among LAB, however, do not universally correlate with the ability to grow in beer. Genome sequencing of the virulent beer spoilage organism Lactobacillus brevis BSO 464 revealed the presence of eight plasmids, with plasmids 1, 2, and 3 containing horA, horC, and hitA, respectively. To investigate the roles that these and the other five plasmids play in L. brevis BSO 464 growth in beer, plasmid curing with novobiocin was used to derive 10 plasmid variants. Multiplex PCRs were utilized to determine the presence or absence of each plasmid, and how plasmid loss affected hop tolerance and growth in degassed (noncarbonated) beer was assessed. Loss of three of the eight plasmids was found to affect hop tolerance and growth in beer. Loss of plasmid 2 (horC and 28 other genes) had the most dramatic effect, with loss of plasmid 4 (120 genes) and plasmid 8 (47 genes) having significant, but smaller, impacts. These results support the contention that genes on mobile genetic elements are essential for bacterial growth in beer and that beer spoilage ability is not dependent solely on the three previously described hop tolerance genes or on the chromosome of a beer spoilage LAB isolate.

A better sequence-read simulator program for metagenomics.

BACKGROUND: There are many programs available for generating simulated whole-genome shotgun sequence reads. The data generated by many of these programs follow predefined models, which limits their use to the authors' original intentions. For example, many models assume that read lengths follow a uniform or normal distribution. Other programs generate models from actual sequencing data, but are limited to reads from single-genome studies. To our knowledge, there are no programs that allow a user to generate simulated data following non-parametric read-length distributions and quality profiles based on empirically-derived information from metagenomics sequencing data. RESULTS: We present BEAR (Better Emulation for Artificial Reads), a program that uses a machine-learning approach to generate reads with lengths and quality values that closely match empirically-derived distributions. BEAR can emulate reads from various sequencing platforms, including Illumina, 454, and Ion Torrent. BEAR requires minimal user input, as it automatically determines appropriate parameter settings from user-supplied data. BEAR also uses a unique method for deriving run-specific error rates, and extracts useful statistics from the metagenomic data itself, such as quality-error models. Many existing simulators are specific to a particular sequencing technology; however, BEAR is not restricted in this way. Because of its flexibility, BEAR is particularly useful for emulating the behaviour of technologies like Ion Torrent, for which no dedicated sequencing simulators are currently available. BEAR is also the first metagenomic sequencing simulator program that automates the process of generating abundances, which can be an arduous task. CONCLUSIONS: BEAR is useful for evaluating data processing tools in genomics. It has many advantages over existing comparable software, such as generating more realistic reads and being independent of sequencing technology, and has features particularly useful for metagenomics work.

Equivalent input produces different output in the UniFrac significance test.

BACKGROUND: UniFrac is a well-known tool for comparing microbial communities and assessing statistically significant differences between communities. In this paper we identify a discrepancy in the UniFrac methodology that causes semantically equivalent inputs to produce different outputs in tests of statistical significance. RESULTS: The phylogenetic trees that are input into UniFrac may or may not contain abundance counts. An isomorphic transform can be defined that will convert trees between these two formats without altering the semantic meaning of the trees. UniFrac produces different outputs for these equivalent forms of the same input tree. This is illustrated using metagenomics data from a lake sediment study. CONCLUSIONS: Results from the UniFrac tool can vary greatly for the same input depending on the arbitrary choice of input format. Practitioners should be aware of this issue and use the tool with caution to ensure consistency and validity in their analyses. We provide a script to transform inputs between equivalent formats to help researchers achieve this consistency.

Transcriptome sequence and plasmid copy number analysis of the brewery isolate Pediococcus claussenii ATCC BAA-344 T during growth in beer.

Growth of specific lactic acid bacteria in beer leads to spoiled product and economic loss for the brewing industry. Microbial growth is typically inhibited by the combined stresses found in beer (e.g., ethanol, hops, low pH, minimal nutrients); however, certain bacteria have adapted to grow in this harsh environment. Considering little is known about the mechanisms used by bacteria to grow in and spoil beer, transcriptome sequencing was performed on a variant of the beer-spoilage organism Pediococcus claussenii ATCC BAA-344(T) (Pc344-358). Illumina sequencing was used to compare the transcript levels in Pc344-358 growing mid-exponentially in beer to those in nutrient-rich MRS broth. Various operons demonstrated high gene expression in beer, several of which are involved in nutrient acquisition and overcoming the inhibitory effects of hop compounds. As well, genes functioning in cell membrane modification and biosynthesis demonstrated significantly higher transcript levels in Pc344-358 growing in beer. Three plasmids had the majority of their genes showing increased transcript levels in beer, whereas the two cryptic plasmids showed slightly decreased gene expression. Follow-up analysis of plasmid copy number in both growth environments revealed similar trends, where more copies of the three non-cryptic plasmids were found in Pc344-358 growing in beer. Transcriptome sequencing also enabled the addition of several genes to the P. claussenii ATCC BAA-344(T) genome annotation, some of which are putatively transcribed as non-coding RNAs. The sequencing results not only provide the first transcriptome description of a beer-spoilage organism while growing in beer, but they also highlight several targets for future exploration, including genes that may have a role in the general stress response of lactic acid bacteria.

RT-qPCR analysis of putative beer-spoilage gene expression during growth of Lactobacillus brevis BSO 464 and Pediococcus claussenii ATCC BAA-344(T) in beer.

Lactic acid bacteria (LAB) contamination of beer presents a continual economic threat to brewers. Interestingly, only certain isolates of LAB can grow in the hostile beer environment (e.g., as studied here, Lactobacillus brevis BSO 464 (Lb464) and a non-ropy isolate of Pediococcus claussenii ATCC BAA-344(T) (Pc344NR)), indicating that significant genetic specialization is required. The genes hitA, horA, horB, horC, and bsrA, which have been proposed to confer beer-spoiling ability to an organism, are suspected of counteracting the antimicrobial effects of hops. However, these genes are not present in the same combination (if at all) across beer-spoiling organisms. As such, we sought to investigate the extent to which these genes participate during Lb464 and Pc344NR mid-logarithmic growth in beer through reverse transcription quantitative PCR analysis. We first determined the optimal reference gene set needed for data normalization and, for each bacterium, established that two genes were needed for accurate assessment of gene expression. Following this, we found that horA expression was induced for Pc344NR, but not for Lb464, during growth in beer. Instead, horC expression was dramatically increased in Lb464 when growing in beer, whereas no change was detected for the other putative beer-spoilage-related genes. This indicates that HorC may be one of the principle mediators enabling growth of Lb464 in beer, whereas in Pc344NR, this may be attributable to HorA. These findings not only reveal that Lb464 and Pc344NR are unique in their beer-specific genetic expression profile but also indicate that a range of genetic specialization exists among beer-spoilage bacteria.

Complete genome sequence of the beer spoilage organism Pediococcus claussenii ATCC BAA-344T.

Pediococcus claussenii is a common brewery contaminant. We have sequenced the chromosome and plasmids of the type strain P. claussenii ATCC BAA-344. A ropy variant was chosen for sequencing to obtain genetic information related to growth in beer, as well as exopolysaccharide and possibly biofilm formation by this organism.

Genome sequence of Lactobacillus rhamnosus ATCC 8530.

Lactobacillus rhamnosus is found in the human gastrointestinal tract and is important for probiotics. We became interested in L. rhamnosus isolate ATCC 8530 in relation to beer spoilage and hops resistance. We report here the genome sequence of this isolate, along with a brief comparison to other available L. rhamnosus genome sequences.

Reclassification of Paralactobacillus selangorensis Leisner et al. 2000 as Lactobacillus selangorensis comb. nov.

The taxonomic status of Paralactobacillus selangorensis is described and, based on evidence presented, transfer of the species to the genus Lactobacillus with the name Lactobacillus selangorensis comb. nov. is proposed. This reclassification is supported by multilocus sequence analysis of the 16S rRNA gene and portions of the cpn60, pheS and rpoA genes. Mode of cell division and existing phenotypic information also show that P. selangorensis cannot be differentiated from the genus Lactobacillus. The type strain of Lactobacillus selangorensis comb. nov. is ATCC BAA-66(T) (=LMG 17710(T) =CIP 106482(T)).

Analysis and comparison of the pan-genomic properties of sixteen well-characterized bacterial genera.

BACKGROUND: The increasing availability of whole genome sequences allows the gene or protein content of different organisms to be compared, leading to burgeoning interest in the relatively new subfield of pan-genomics. However, while several studies have analyzed protein content relationships in specific groups of bacteria, there has yet to be a study that provides a general characterization of protein content relationships in a broad range of bacteria. RESULTS: A variation on reciprocal BLAST hits was used to infer relationships among proteins in several groups of bacteria, and data regarding protein conservation and uniqueness in different bacterial genera are reported in terms of "core proteomes", "unique proteomes", and "singlets". We also analyzed the relationship between protein content similarity and the percent identity of the 16S rRNA gene in pairs of bacterial isolates from the same genus, and found that the strength of this relationship varied substantially depending on the genus, perhaps reflecting different rates of genome evolution and/or horizontal gene transfer. Finally, core proteomes and unique proteomes were used to study the proteomic cohesiveness of several bacterial species, revealing that some bacterial species had little cohesiveness in their protein content, with some having fewer proteins unique to that species than randomly-chosen sets of isolates from the same genus. CONCLUSIONS: The results described in this study aid our understanding of protein content relationships in different bacterial groups, allowing us to make further inferences regarding genome-environment relationships, genome evolution, and the soundness of existing taxonomic classifications.

Thioredoxin system from Deinococcus radiodurans.

This paper describes the cloning, purification, and characterization of thioredoxin (Trx) and thioredoxin reductase (TrxR) and the structure determination of TrxR from the ionizing radiation-tolerant bacterium Deinococcus radiodurans strain R1. The genes from D. radiodurans encoding Trx and TrxR were amplified by PCR, inserted into a pET expression vector, and overexpressed in Escherichia coli. The overexpressed proteins were purified by metal affinity chromatography, and their activity was demonstrated using well-established assays of insulin precipitation (for Trx), 5,5'-dithiobis(2-nitrobenzoic acid) (DTNB) reduction, and insulin reduction (for TrxR). In addition, the crystal structure of oxidized TrxR was determined at 1.9-A resolution. The overall structure was found to be very similar to that of E. coli TrxR and homodimeric with both NADPH- and flavin adenine dinucleotide (FAD)-binding domains containing variants of the canonical nucleotide binding fold, the Rossmann fold. The K(m) (5.7 muM) of D. radiodurans TrxR for D. radiodurans Trx was determined and is about twofold higher than that of the E. coli thioredoxin system. However, D. radiodurans TrxR has a much lower affinity for E. coli Trx (K(m), 44.4 muM). Subtle differences in the surface charge and shape of the Trx binding site on TrxR may account for the differences in recognition. Because it has been suggested that TrxR from D. radiodurans may have dual cofactor specificity (can utilize both NADH and NADPH), D. radiodurans TrxR was tested for its ability to utilize NADH as well. Our results show that D. radiodurans TrxR can utilize only NADPH for activity.