Bacterial Population Genomics
Bacterial Population Genomics - Related Videos
08:03
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
0 Views •
Cited by 2 •
2021
This analytical computational platform provides practical guidance for microbiologists, ecologists, and epidemiologists interested in bacterial population genomics. Specifically, the work presented here demonstrated how to perform: i) phylogeny-guided mapping of hierarchical genotypes; ii) frequency-based analysis of genotypes; iii) kinship and clonality analyses; iv) identification of lineage differentiating accessory loci.
03:27
Establishing a Defined Gut Bacterial Population in Adult Mosquitoes
0 Views •
2026
Source: Liu, X., et al. A Bacterial Oral Feeding Assay with Antibiotic-Treated Mosquitoes. J. Vis. Exp. (2020)This video demonstrates the depletion of native gut microbiota in mosquitoes using an antibiotic-containing sucrose solution. This is followed by controlled recolonization with a bacterial suspension delivered through a membrane feeding system to establish a defined bacterial population in the mosquito gut.
10:44
Generating Whole Bacterial Genomes from Clinical Samples using a Target Enrichment Workflow
0 Views •
Cited by 1 •
2025
Here, we present a protocol to enable whole-genome sequencing of bacterial sexually transmitted infections from clinical samples using target enrichment. This novel, syndromic panel-based method overcomes challenges of abundant human DNA and low bacterial loads, facilitating genomic surveillance for Chlamydia trachomatis, Neisseria gonorrhoeae, Treponema pallidum, and Mycoplasma genitalium.
06:45
Monitoring Intraspecies Competition in a Bacterial Cell Population by Cocultivation of Fluorescently Labelled Strains
0 Views •
Cited by 8 •
2014
Bacteria may accumulate either detrimental or beneficial mutations during their lifetime. In a population of cells individuals that have accumulated beneficial mutations may rapidly outcompete their fellows. Here we present a simple procedure to visualize intraspecies competition in a bacterial cell population over time using fluorescently labeled...
08:31
Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
0 Views •
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.
FAQs
Mutation and recombination create different patterns of genetic variation that statistical analysis must distinguish. Single-nucleotide polymorphisms can mark differences among genomes, while recombination may introduce shared sequence changes that do not reflect simple descent from one lineage. Accounting for both processes improves estimates of relatedness, population structure, and genetic change over time.
Researchers compare genetic variants across sequenced bacterial genomes and apply probability models to estimate which isolates are more closely related. These comparisons can reveal clonal lineages, groups of genetically similar organisms, and broader population structure. The resulting patterns help connect genomic differences with evolutionary history and ecological distribution.
Comparative statistics can identify genomic patterns that are consistent with nonrandom genetic change, including signatures of natural selection. Analysts evaluate variation across genomes and populations rather than interpreting an individual mutation in isolation. This approach helps distinguish broader evolutionary signals from ordinary genetic differences and supports interpretation of how bacterial populations change.
A typical study begins by sequencing bacterial genomes from the population or set of isolates under investigation. Researchers then identify genetic variants, account for mutation and recombination, and use statistical analysis to estimate relatedness and population structure. Finally, they interpret these results alongside evolutionary, ecological, or disease-transmission questions.
During an outbreak investigation, genome comparisons can show whether bacterial isolates belong to the same clonal lineage or represent genetically distinct groups. Statistical estimates of relatedness and population structure provide evidence about possible transmission connections. These results help investigators distinguish linked cases from unrelated infections and strengthen interpretation of disease spread.
Bacterial population genomics can connect resistance-associated genetic variation with patterns across bacterial populations. Statistical comparisons help assess whether related lineages share resistance traits and how those traits are distributed over time. In surveillance, these findings support evaluation of resistance spread and can inform evidence-based strategies for managing infectious disease.