Dataset Information

Combined Application of High-Throughput Sequencing and Metabolomics Reveals Metabolically Active Microorganisms During Panxian Ham Processing.

ABSTRACT: Panxian ham, a traditional Chinese dry-cured ham, is protected by national geographical indication. Similar to other fermented foods, the microbial population of dry-cured ham is pivotal to taste and flavor formation. This study aimed to establish the relationship between microorganisms and metabolites during the spontaneous fermentation of Panxian ham. Multivariate analysis based on metabolomics data revealed that continuous metabolic changes occurred during the entire fermentation process, with the most significant changes occurring in the initial stage of ripening. Thirty-one significantly different metabolites (SDMs) were identified as discriminant factor, and pathway analysis suggested that these metabolites were involved in 30 pathways, including alanine, aspartate, and glutamate metabolism; glycine, serine, and threonine metabolism; and arginine and proline metabolism. Microbial community analysis using the Illumina MiSeq platform indicated that the bacterial community was more complex than the fungal community, and their succession regulation differed during processing. At the genus level, 11 bacteria and five fungi were identified as core microbes, of which Staphylococcus was the dominant bacteria and Debaryomyces and Aspergillus were the dominant fungi. Further, statistical redundancy analysis (RDA) indicated that Staphylococcus, Debaryomyces, and Chromohalobacter promoted the production of amino and fatty acids; Cobetia and Aspergillus were associated with sugar metabolism, and Kushneria, Penicillium, and Yamadazyma were closely related with organic acids. These findings provide fundamental knowledge regarding the metabolically active microorganisms in Panxian ham, helping industrial processors to develop effective strategies for standardizing quality parameters.

SUBMITTER: Mu Y

PROVIDER: S-EPMC6966718 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Combined Application of High-Throughput Sequencing and Metabolomics Reveals Metabolically Active Microorganisms During Panxian Ham Processing.

Mu Yu Y Su Wei W Mu Yingchun Y Jiang Li L

Frontiers in microbiology 20200110

Panxian ham, a traditional Chinese dry-cured ham, is protected by national geographical indication. Similar to other fermented foods, the microbial population of dry-cured ham is pivotal to taste and flavor formation. This study aimed to establish the relationship between microorganisms and metabolites during the spontaneous fermentation of Panxian ham. Multivariate analysis based on metabolomics data revealed that continuous metabolic changes occurred during the entire fermentation process, wit ...[more]

PMID: 31998279

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Project description:(1) Background: Mianning ham is a dry-cured ham from Southwest China, known for its distinct regional characteristics and delicious taste. It is particularly favored by consumers due to its safety, as no artificial nitrites are added during processing. The microbial changes during its different processing stages significantly influence the final product's flavor. This study aims to investigate the changes in microbial communities and flavor compounds across the nine stages of Mianning ham production, from raw material preparation to salting, drying, fermentation, and maturation, using 16S and ITS sequencing, as well as solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS). The goal is to explore the correlation between these changes and provide a basis for process improvement from the initial raw material preparation. (2) Results: The microbiota of Mianning ham across different processing stages mainly consisted of Proteobacteria, Firmicutes, and Ascomycota. A total of 324 volatile compounds were identified, of which 27 were key contributors to the ham's flavor. Aldehydes contributed the most to flavor, with octanal, trans-2-nonenal, and trans, trans-2,4-decadienal being the most significant contributors at various stages. Mature Mianning ham, fermented for 1-3 years, exhibited fresh grass and earthy aromas, buttery and fatty flavors, and a distinctive roasted potato note. Correlation analysis revealed that Cobetia was the primary bacterial contributor to the main flavor compounds, especially prominent in the second year of fermentation. Among fungi, Yamadazyma and Aspergillus positively influenced several key aldehyde flavor compounds throughout the processing stages, significantly contributing to the flavor profile of Mianning ham. (3) Conclusions: Correlation analysis showed that the Mianning ham that matured for two years had the richest and most characteristic flavor. The positive and consistent impact of fungi on the ham's flavor suggests that they may warrant further research and application in Mianning ham production. This provides a theoretical basis for improving the flavor quality and enhancing the market competitiveness of Mianning ham. One of the key features of Mianning ham is its substantial accumulation of hydrocarbons, which surpasses that of hams from other regions in China. A notable characteristic of Mianning ham processing is the absence of artificially added nitrites as antioxidants and color fixatives. Whether this absence is a contributing factor to the significant accumulation of hydrocarbons warrants further investigation.

Project description:BackgroundIn addition to heterogeneity and artificial selection, natural selection is one of the forces used to combat climate change and improve agrobiodiversity in evolutionary plant breeding. Accurate identification of the specific genomic effects of natural selection will likely accelerate transfer between populations. Thus, insights into changes in allele frequency, adequate population size, gene flow and drift are essential. However, observing such effects often involves a trade-off between costs and resolution when a large sample of genotypes for many loci is analysed. Pool genotyping approaches achieve high resolution and precision in estimating allele frequency when sequence coverage is high. Nevertheless, high-coverage pool sequencing of large genomes is expensive.ResultsThree pool samples (n = 300, 300, 288) from a barley backcross population were generated to assess the population's allele frequency. The tested population (BC2F21) has undergone 18 generations of natural adaption to conventional farming practice. The accuracies of estimated pool-based allele frequencies and genome coverage yields were compared using three next-generation sequencing genotyping methods. To achieve accurate allele frequency estimates with low sequence coverage, we employed a haplotyping approach. Low coverage allele frequencies of closely located single polymorphisms were aggregated into a single haplotype allele frequency, yielding 2-to-271-times higher depth and increased precision. When we combined different haplotyping tactics, we found that gene and chip marker-based haplotype analyses performed equivalently or better compared with simple contig haplotype windows. Comparing multiple pool samples and referencing against an individual sequencing approach revealed that whole-genome pool re-sequencing (WGS) achieved the highest correlation with individual genotyping (≥ 0.97). In contrast, transcriptome-based genotyping (MACE) and genotyping by sequencing (GBS) pool replicates were significantly associated with higher error rates and lower correlations, but are still valuable to detect large allele frequency variations.ConclusionsThe proposed strategy identified the allele frequency of populations with high accuracy at low cost. This is particularly relevant to evolutionary plant breeding of crops with very large genomes, such as barley. Whole-genome low coverage re-sequencing at 0.03 × coverage per genotype accurately estimated the allele frequency when a loci-based haplotyping approach was applied. The implementation of annotated haplotypes capitalises on the biological background and statistical robustness.

Dataset Information

Combined Application of High-Throughput Sequencing and Metabolomics Reveals Metabolically Active Microorganisms During Panxian Ham Processing.

Publications

Combined Application of High-Throughput Sequencing and Metabolomics Reveals Metabolically Active Microorganisms During Panxian Ham Processing.

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