Microbial Communities on Samples of Commercially Available Fresh-Consumed Leafy Vegetables and Small Berries

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Abstract

Microbial communities on fresh-consumed plant products are an important predictor of quality and safety for the consumer. Totally, 45 samples of berry fruits (8 blackberries, 9 blueberries, 8 strawberries, 8 raspberries, 12 currants) and 40 samples of leafy vegetables (20 lettuce, 6 cornsalad, 8 rocket, 8 spinach) were analyzed using cultivation and DNA-depended methods. Total aerobic count, coliforms, and yeasts were significantly lower in fruits while counts of filamentous fungi were similar. Pantoea, Enterobacter, and Klebsiella were the most common colonies grown on VRBL agar. Salmonella was detected in single sample of cornsalad using qPCR but no sample contained Escherichia coli harboring stx1, stx2 and intimin genes. Sequencing of V4 region of bacteria 16S rRNA and ITS2 region of fungi amplified from plant tissue-extracted DNA confirmed different composition of fruit and vegetable microbiome. Pre-enrichment of bacteria in phosphate buffered water allowed deeper analysis of Enterobacteriaceae using V4–V5 region of 16S rRNA while differences among communities were described similarly. Pantoea, Klebsiella, or Staphylococcus were more frequent in berries while Pseudomonas, Flavobacterium, or Sphingobacterium in leafy vegetables. Comparison of inner and outer leaves of head-forming lettuces (6 iceberg, 5 romain) showed that outer leaves are colonized by more bacteria with higher diversity. Microbiological safety of fresh production requires more attention as the potentially pathogenic bacteria were detected, particularly in leafy vegetables. However, the true pathogenicity of such bacteria needs further research.

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MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

Kazutaka Katoh, Daron Standley (2013)

We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.

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Metagenomic biomarker discovery and explanation

Nicola Segata, Jacques Izard, Levi Waldron … (2011)

This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.

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Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

Qiong Wang, George Garrity, James Tiedje … (2007)

The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.