Metadata Analysis Approaches for Understanding and Improving the Functional Involvement of Rumen Microbial Consortium in Digestion and Metabolism of Plant Biomass

Abstract

Rumen is one of the most complex gastro-intestinal system in ruminating animals. With bountiful of microorganisms supporting in breakdown and consumption of minerals and nutrients from the complex plant biomass. It is predicted that a table spoon of ruminal fluid can reside up to 150 billion microorganisms including various species of bacteria, fungi and protozoa. Several studies in the past have extensively explained about the structural and functional physiology of the rumen. Studies based on rumen and its microbiota has increased significantly in the last decade to understand and reveal applications of the rumen microbiota in food processing, pharmaceutical, biofuel and biorefining industries. Recent high-throughput meta-genomic and proteomic studies have revealed humongous information on rumen microbial diversity. In this study, we have extensively reviewed and reported present-day's progress in understanding the rumen microbial diversity. As of today, NCBI resides about 821,870 records based on rumen with approximately 889 genome sequencing studies. We have retrieved all the rumen-based records from NCBI and extensively catalogued the rumen microbial diversity and the corresponding genomic and proteomic studies respectively. Also, we have provided a brief inventory of metadata analysis software packages and reviewed the metadata analysis approaches for understanding the functional involvement of these microorganisms. Knowing and understanding the present progress on rumen microbiota and performing metadata analysis studies will significantly benefit the researchers in identifying the molecular mechanisms involved in plant biomass degradation. These studies are also necessary for developing highly efficient microorganisms and enzyme mixtures for enhancing the benefits of cattle-feedstock and biofuel industries.

Keywords: Bacteria; Fungi; Genomic; Microbiota; Proteomic; Protozoa.; Ruminal fluid; Ruminating animals.

Figure 1

Pictorial representation of rumen and the process of digestion and absorption of the food material in ruminating animals [Note: The boxes are colored to represent the food passage from mouth to the rumen].

Figure 2

Breakdown products obtained from the process of fermentation by rumen microbiota. [Note: The uncolored boxes are the macromolecules and the blue colored boxes represent the products of metabolism].

Figure 3

The major microorganism species reported in the previous studies and classified based on the substrates they degrade.

Figure 4

Pictorial representation of the present days collection a) the number of records and datasets in NCBI database based on the term “Rumen”, b) briefly lists details of the genomic and metagenomic sequencing studies i) sequencing institution, ii) level of assembly and iii) the classification of assembled genomes into archaea and bacteria groups and c) shows the division of assembled genomes of microorganisms at genus level (A, B, D, E and G - proteobacteria represents α, β, δ, γ, £- proteobacteria). [Note: The color gradient used for the images A and B were generated using Microsoft Excel with red color represents lowest count, green color represents highest count and yellow color represents for intermediate count. Especially for figure 4A was gradient colored based for each section separately].

Figure 5

The project data details of rumen microorganisms and the highly occurring genus in the rumen isolates. [Note: The color gradient used for the images A and B were generated using Microsoft Excel with red color represents lowest count, green color represents highest count and yellow color represents for intermediate count].

Figure 6

Pictorial representation of metadata analysis workflow applied for analyzing and understanding the genomic metadata analysis approach;

Figure 7

Pictorial representation of metadata analysis workflow applied for analyzing and understanding the proteomic metadata analysis approach.