Microbial Genomes
Microbial Genomes - Related Videos
01:08
Evolution of Microbial Genome
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2026
Microbial genome evolution is a highly dynamic process shaped by continual gene gain and loss across species and strains. This genomic flexibility allows microorganisms to adapt rapidly to environmental pressures and interactions with other organisms. Central to understanding this diversity is the distinction between the core and pan genomes.The core genome comprises the genes shared by all sampled strains of a species, representing essential functions needed for fundamental cellular processes.
08:31
Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
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Cited by 2 •
2013
Single Virus Genomics (SVG) is a method to isolate and amplify the genomes of single virons. Viral suspensions of a mixed assemblage are sorted using flow cytometry onto a microscope slide with discrete wells containing agarose, thereby capturing the virion and reducing genome shearing during downstream processing. Whole genome amplification is achieved using multiple displacement amplification (MDA) resulting in genomic material that is suitable for sequencing.
12:37
Pyrosequencing for Microbial Identification and Characterization
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Cited by 21 •
2013
Pyrosequencing is a versatile technique that facilitates microbial genome sequencing that can be used to identify bacterial species, discriminate bacterial strains, and detect genetic mutations that confer resistance to anti-microbial agents. In this video, the procedure for microbial amplicon generation, amplicon pyrosequencing, and DNA sequence analysis will be demonstrated.
21:02
Investigating the Microbial Community in the Termite Hindgut - Interview
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2007
Jared Leadbetter explains why the termite-gut microbial community is an excellent system for studying the complex interactions between microbes. The symbiotic relationship existing between the host insect and lignocellulose-degrading gut microbes is explained, as well as the industrial uses of these microbes for degrading plant biomass and generating biofuels.
FAQs
Genome sequencing supplies the information needed to examine a microorganism’s genetic content, while computational annotation identifies genetic features and predicts their roles. Together, these steps connect DNA sequences with possible biological functions rather than treating sequence data as an inventory alone. The resulting interpretation can clarify genes associated with growth, metabolism, adaptation, or interactions with hosts and environments.
Genes encode functions that influence microbial growth, metabolism, adaptation, and interactions with hosts or environments. Regulatory sequences help determine how genetic information is expressed, so genome analysis considers more than the presence of genes alone. Examining both types of sequence can improve predictions about how a microorganism uses its genetic information under different biological or environmental conditions.
Comparative analysis can reveal evolutionary relationships as well as differences in metabolic capabilities, antibiotic-resistance determinants, and environmental adaptation. These contrasts help connect shared or distinct genetic features with the ways microorganisms live and respond to their surroundings. Such comparisons are useful for interpreting microbial diversity and identifying functions that may distinguish related organisms.
Antibiotic-resistance determinants are genetic features that can be identified and compared across microbial genomes. Their distribution provides information relevant to infectious-disease research and can help distinguish microorganisms with different predicted resistance-associated capacities. Studying these determinants alongside broader genome differences places resistance within the organism’s overall genetic and biological context rather than examining it in isolation.
A typical analysis begins by obtaining genome sequence information, followed by computational annotation to identify genetic features and predict their roles. Researchers can then compare the resulting information among microorganisms or interpret it in relation to hosts and environments. This workflow supports conclusions about growth, metabolism, adaptation, evolutionary relationships, and antibiotic-resistance determinants.
Researchers apply microbial genome analysis when they need to investigate infectious disease, characterize microbiomes, study environmental microorganisms, or examine organisms with potential biotechnological value. The analysis can provide clues about metabolic capabilities, adaptation, host interactions, and resistance-associated genetic features. These findings support both basic biological research and efforts to manage beneficial or harmful microorganisms.
Genome-based analysis helps examine how microorganisms are adapted to particular environments and how their genetic features may contribute to interactions within microbial communities or with hosts. In microbiome studies, comparisons can clarify the capabilities represented by different microorganisms. In environmental monitoring, the same information can help assess microbial composition, functions, and potential biological significance.