Cheese rinds host a specific microbiota composed of both prokaryotes (such as Actinobacteria, Firmicutes and Proteobacteria) and eukaryotes (primarily yeasts and moulds). By combining modern molecular biology tools with conventional, culture-based techniques, it has now become possible to create a catalogue of the biodiversity that inhabits this special environment. Here, we review the microbial genera detected on the cheese surface and highlight the previously unsuspected importance of non-inoculated microflora--raising the question of the latter's environmental sources and their role in shaping microbial communities. There is now a clear need to revise the current view of the cheese rind ecosystem (i.e. that of a well-defined, perfectly controlled ecosystem). Inclusion of these new findings should enable us to better understand the cheese-making process.
Editor: Gary KingKeywords a-subunit of the particulate methane monooxygenase; a-subunit of the methylcoenzyme M reductase; aerobic methanotrophy; methanogenesis.
AbstractLake Pavin is a meromictic crater lake located in the French Massif Central area. In this ecosystem, most methane (CH 4 ) produced in high quantity in the anoxic bottom layers, and especially in sediments, is consumed in the water column, with only a small fraction of annual production reaching the atmosphere. This study assessed the diversity of methanogenic and methanotrophic populations along the water column and in sediments using PCR and reverse transcription-PCR-based approaches targeting functional genes, i.e. pmoA (a-subunit of the particulate methane monooxygenase) for methanotrophy and mcrA (a-subunit of the methylcoenzyme M reductase) for methanogenesis as well as the phylogenetic 16S rRNA genes. Although methanogenesis rates were much higher in sediments, our results confirm that CH 4 production also occurs in the water column where methanogens were almost exclusively composed of hydrogenotrophic methanogens, whereas both hydrogenotrophs and acetotrophs were almost equivalent in the sediments. Sequence analysis of markers, pmoA and the 16S rRNA gene, suggested that Methylobacter may be an important group actively involved in CH 4 oxidation in the water column. Two main phylotypes were characterized, one of which could consume CH 4 under conditions where the oxygen amount is undetectable.
Cheese ripening is a complex biochemical process driven by microbial communities composed of both eukaryotes and prokaryotes. Surface-ripened cheeses are widely consumed all over the world and are appreciated for their characteristic flavor. Microbial community composition has been studied for a long time on surface-ripened cheeses, but only limited knowledge has been acquired about its in situ metabolic activities. We applied metagenomic, metatranscriptomic and biochemical analyses to an experimental surface-ripened cheese composed of nine microbial species during four weeks of ripening. By combining all of the data, we were able to obtain an overview of the cheese maturation process and to better understand the metabolic activities of the different community members and their possible interactions. Furthermore, differential expression analysis was used to select a set of biomarker genes, providing a valuable tool that can be used to monitor the cheese-making process.
Escherichia coli O157:H7 is a major foodborne human pathogen causing disease worldwide. Cattle are a major reservoir for this pathogen and those that shed E. coli O157:H7 at >104 CFU/g feces have been termed “super-shedders”. A rich microbial community inhabits the mammalian intestinal tract, but it is not known if the structure of this community differs between super-shedder cattle and their non-shedding pen mates. We hypothesized that the super-shedder state is a result of an intestinal dysbiosis of the microbial community and that a “normal” microbiota prevents E. coli O157:H7 from reaching super-shedding levels. To address this question, we applied 454 pyrosequencing of bacterial 16S rRNA genes to characterize fecal bacterial communities from 11 super-shedders and 11 contemporary pen mates negative for E. coli O157:H7. The dataset was analyzed by using five independent clustering methods to minimize potential biases and to increase confidence in the results. Our analyses collectively indicated significant variations in microbiome composition between super-shedding and non-shedding cattle. Super-shedders exhibited higher bacterial richness and diversity than non-shedders. Furthermore, seventy-two operational taxonomic units, mostly belonging to Firmicutes and Bacteroidetes phyla, were identified showing differential abundance between these two groups of cattle. The operational taxonomic unit affiliation provides new insight into bacterial populations that are present in feces arising from super-shedders of E. coli O157:H7.
High-quality annotation of microsporidian genomes is essential for understanding the biological processes that govern the development of these parasites. Here we present an improved structural annotation method using transcriptional DnA signals. We apply this method to re-annotate four previously annotated genomes, which allow us to detect annotation errors and identify a significant number of unpredicted genes. We then annotate the newly sequenced genome of Anncaliia algerae. A comparative genomic analysis of A. algerae permits the identification of not only microsporidian core genes, but also potentially highly expressed genes encoding membrane-associated proteins, which represent good candidates involved in the spore architecture, the invasion process and the microsporidianhost relationships. Furthermore, we find that the ten-fold variation in microsporidian genome sizes is not due to gene number, size or complexity, but instead stems from the presence of transposable elements. such elements, along with kinase regulatory pathways and specific transporters, appear to be key factors in microsporidian adaptive processes.
Next-generation sequencing (NGS) allows faster acquisition of metagenomic data, but complete exploration of complex ecosystems is hindered by the extraordinary diversity of microorganisms. To reduce the environmental complexity, we created an innovative solution hybrid selection (SHS) method that is combined with NGS to characterize large DNA fragments harbouring biomarkers of interest. The quality of enrichment was evaluated after fragments containing the methyl coenzyme M reductase subunit A gene (mcrA), the biomarker of methanogenesis, were captured from a Methanosarcina strain and a metagenomic sample from a meromictic lake. The methanogen diversity was compared with direct metagenome and mcrA-based amplicon pyrosequencing strategies. The SHS approach resulted in the capture of DNA fragments up to 2.5 kb with an enrichment efficiency between 41 and 100%, depending on the sample complexity. Compared with direct metagenome and amplicons sequencing, SHS detected broader mcrA diversity, and it allowed efficient sampling of the rare biosphere and unknown sequences. In contrast to amplicon-based strategies, SHS is less biased and GC independent, and it recovered complete biomarker sequences in addition to conserved regions. Because this method can also isolate the regions flanking the target sequences, it could facilitate operon reconstructions.
SummaryDesigning environmental DNA microarrays that can be used to survey the extreme diversity of microorganisms existing in nature, represents a stimulating challenge in the field of molecular ecology. Indeed, recent efforts in metagenomics have produced a substantial amount of sequence information from various ecosystems, and will continue to accumulate large amounts of sequence data given the qualitative and quantitative improvements in the next-generation sequencing methods. It is now possible to take advantage of these data to develop comprehensive microarrays by using explorative probe design strategies. Such strategies anticipate genetic variations and thus are able to detect known and unknown sequences in environmental samples. In this review, we provide a detailed overview of the probe design strategies currently available to construct both phylogenetic and functional DNA microarrays, with emphasis on those permitting the selection of such explorative probes. Furthermore, exploration of complex environments requires particular attention on probe sensitivity and specificity criteria. Finally, these innovative probe design approaches require exploiting newly available high-density microarray formats.
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