Humulus lupulus and microbes: Exploring biotic causes for hop creep.

BACKGROUND: Hop creep continues to present an unresolved issue for the brewing industry, specifically stemming from those hops added to beer during fermentation. Hops have been found to contain four dextrin-degrading enzymes: alpha amylase, beta amylase, limit dextrinase, and an amyloglucosidase. One recent hypothesis predicts that these dextrin-degrading enzymes could originate from microbes rather than the hop plant itself. SCOPE AND APPROACH: This review begins by describing how hops are processed and used in the brewing industry. It will then discuss hop creep's origins with a new beer style, antimicrobial factors from hops and resistance mechanisms that bacteria use to counter them, and finally microbial communities that inhabit hops, focusing on whether they can produce the starch degrading enzymes which drive hop creep. After initial identification, microbes with possible links to hop creep were then run through several databases to search the genomes (if available) and for those specific enzymes. KEY FINDINGS AND CONCLUSIONS: Several bacteria and fungi contain alpha amylase as well as unspecified glycosyl hydrolases, but only one contains beta amylase. Finally, this paper closes with a short summary of how abundant these organisms typically are in other flowers.

Impact of Harvest on Switchgrass Leaf Microbial Communities.

Switchgrass is a promising feedstock for biofuel production, with potential for leveraging its native microbial community to increase productivity and resilience to environmental stress. Here, we characterized the bacterial, archaeal and fungal diversity of the leaf microbial community associated with four switchgrass (Panicum virgatum) genotypes, subjected to two harvest treatments (annual harvest and unharvested control), and two fertilization levels (fertilized and unfertilized control), based on 16S rRNA gene and internal transcribed spacer (ITS) region amplicon sequencing. Leaf surface and leaf endosphere bacterial communities were significantly different with Alphaproteobacteria enriched in the leaf surface and Gammaproteobacteria and Bacilli enriched in the leaf endosphere. Harvest treatment significantly shifted presence/absence and abundances of bacterial and fungal leaf surface community members: Gammaproteobacteria were significantly enriched in harvested and Alphaproteobacteria were significantly enriched in unharvested leaf surface communities. These shifts were most prominent in the upland genotype DAC where the leaf surface showed the highest enrichment of Gammaproteobacteria, including taxa with 100% identity to those previously shown to have phytopathogenic function. Fertilization did not have any significant impact on bacterial or fungal communities. We also identified bacterial and fungal taxa present in both the leaf surface and leaf endosphere across all genotypes and treatments. These core taxa were dominated by Methylobacterium, Enterobacteriaceae, and Curtobacterium, in addition to Aureobasidium, Cladosporium, Alternaria and Dothideales. Local core leaf bacterial and fungal taxa represent promising targets for plant microbe engineering and manipulation across various genotypes and harvest treatments. Our study showcases, for the first time, the significant impact that harvest treatment can have on bacterial and fungal taxa inhabiting switchgrass leaves and the need to include this factor in future plant microbial community studies.

Shotgun metagenomic data of root endophytic microbiome of maize (Zea mays L.).

This dataset represents the root endophytic microbial community profile of maize (Zea mays L.), one of the largest food crops in South Africa, using a shotgun metagenomic approach. To the best of our understanding, this is the first account showcasing the endophytic microbial diversity in maize plants via the shotgun metagenomics approach. High throughput sequencing of the whole DNA from the community was carried out using NovaSeq 6000 system (Illumina). The data obtained consists of 10,915,268 sequences accounting for 261,906,948 bps with an average length of 153 base pairs and 43% Guanine+Cytosine content. The metagenome data can be accessed at the National Centre for Biotechnology Information SRA registered with the accession number PRJNA607664. Community analysis was done using an online server called MG-RAST, which showed that 0.12% of the sequences were archaeal associated, eukaryotes were 15.06%, while 84.77% were classified as bacteria. A sum of 28 bacterial, 22 eukaryotic and 4 archaeal phyla were identified. The predominant genera were Bacillus (16%), Chitinophaga (12%), Flavobacterium (4%), Chryseobacterium (4%), Paenibacillus (4%), Pedobacter (3%) and Alphaproteobacteria (3%). Annotation using Cluster of Orthologous Group (COG) revealed that 41.47% of the sequenced data were for metabolic function, 24.10% for chemical process and signaling, while 17.43% of the sequences were in the poorly characterized group. Annotation using the subsystem method showed that 18% of the sequences were associated with carbohydrates, 9% were for clustering-based subsystems, and 9% contain genes coding for amino acids and derivatives, which might be beneficial in plant growth and health improvement.