Search NASA⌕ Search

DOE OSTI · 1893878

BMC Caller: a webtool to identify and analyze bacterial microcompartment types in sequence data

Abstract

Bacterial microcompartments (BMCs) are protein-based organelles found across the bacterial tree of life. They consist of a shell, made of proteins that oligomerize into hexagonally and pentagonally shaped building blocks, that surrounds enzymes constituting a segment of a metabolic pathway. The proteins of the shell are unique to BMCs. They also provide selective permeability; this selectivity is dictated by the requirements of their cargo enzymes. We have recently surveyed the wealth of different BMC types and their occurrence in all available genome sequence data by analyzing and categorizing their components found in chromosomal loci using HMM (Hidden Markov Model) protein profiles. To make this a “do-it yourself” analysis for the public we have devised a webserver, BMC Caller (https://bmc-caller.prl.msu.edu), that compares user input sequences to our HMM profiles, creates a BMC locus visualization, and defines the functional type of BMC, if known. Shell proteins in the input sequence data are also classified according to our function-agnostic naming system and there are links to similar proteins in our database as well as an external link to a structure prediction website to easily generate structural models of the shell proteins, which facilitates understanding permeability properties of the shell. Additionally, the BMC Caller website contains a wealth of information on previously analyzed BMC loci with links to detailed data for each BMC protein and phylogenetic information on the BMC shell proteins. Our tools greatly facilitate BMC type identification to provide the user information about the associated organism’s metabolism and enable discovery of new BMC types by providing a reference database of all currently known examples.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sutter, Markus, Kerfeld, Cheryl A.. 2022-04-28. BMC Caller: a webtool to identify and analyze bacterial microcompartment types in sequence data. https://doi.org/10.1186/s13062-022-00323-z

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-resolved insights into microbial diversity and elemental cycling in Winogradsky columns

We retained 18 MAGs with ≥50% completion and <10% contamination (i.e., at least medium quality). Of these, 10 had >90% completion and <5% contamination; however, only one (Paceibacteria Bin.003_MG) can be described as high-quality, as the others lacked a full suite of 5S, 16S, and 23S rRNA genes. To maximize the diversity of our recovered MAGs, we also retained one MAG (Chromatiaceae Bin.008_AM) with >40% (but less than 50%) completion and <5% contamination, as well as one (Rhodopseudomonas Bin.015_MK) with >90% completion and <20% (but>10%) contamination. Interestingly, significant chimerism was not detected in this MAG (40) , suggesting that the elevated contamination (20%) may instead reflect two closely related strains collapsing into a single bin. Consistent with this, contig coverage was bimodal, with roughly 17% of the assembly at ~115x and the remaining 83% at ~282x, while GC content remained uniform across both groups (~64%), arguing against contamination from a taxonomically distinct source.

59 BASIC BIOLOGICAL SCIENCES↗