Quantifying Infectious Disease / Methodology (Exam 1)

Parasites

40% of know species are parasitic

Parasites are unseen biodiversity

capture and dissect

traditional approach to look for parasites under a microscope

- to be effective you have to be thorough

hosts don't always need to be sacrificed

- swabbing frogs

- floating eggs in fecal samples

- dust ruffling

- blood samples

Opportunistic sampling

Majority of sampling

- ex. a dead oarfish washed up in CA and a parisitologically surveyed

small size of parasites can make it hard to distinguish species

Cryptic species

those who are difficult to distinguish morphologically

DNA sequencing

- if you extract DNA from a sample of host tissue you get all DNA present including parasite DNA if host was infected

Polymerase chain reaction (PCR)

- replicate og DNA

- by doing this many many times you can build up a chunk of DNA (essentially doubling)

- good for sequencing but be aware of contamination

- if parasite DNA was present in sample, amplicon will be formed by PCR and will be visible when stained --> assumes test is very sensitive

Sensitivity

proportion of infected individuals that test positive

low sensitivity = many false negatives

Specificity

proportion of uninfected individuals that test negative

low specificity = false positives

Benefits of PCR and Sanger Sequencing Approach:

- Only tiny amounts of parasite DNA/RNA necessary for detection

- Sequence data allows for easier ID than traditional morphology based methods

- Sequence data allows for phylogenetic relationships to be established and potentially population genetic analysis to be conducted

Limitations of PCR & Sanger sequencing approach:

- You still have to extract DNA from the right tissue

- Limited by sequences that already exist for comparison and primer design (to design primers you need a target)

- hard to sequence a large genome with PCR and Sanger Sequencing

Next generation sequencing

- new sequencing approach within the last 15 years

- massive increase in sequencing output (multiple genomes can be sequenced in much shorter amounts of time)

- reduction in cost

- reads are short and difficult to assemble

Next gen sequencing: how it works

- genomic DNA sheared to specific size

- sequence reaction samples are identified after pooling and binded to the flow cell which are ligated to the sheared DNA to make

challenge: whole genome gets broken and it's hard to put back together

- once you get short reads you can map them to your reference genome

Metagenomics

- next gen sequencing has allowed metagenomics

- ID of genes from multiple species in a single DNA sample

- ID is done by comparing sequences to database

Sequence capture

- RNA probes that match the parasite genome are mixed into the DNA sample --> bind to the parasite DNA and host DNA is washed away

- Used to sequence mitochondrial genome of P. falciparum from DNA extracted from teeth from graves from 1st - 2nd centuries CE in Italy

Selective whole genome amplification

- design primers that bind the parasite more often than the host, amplify whole genome with phi29 enzyme

Contamination

- makes it difficult to sequence the genomes of parasites and pathogens particularly those that cannot be cultured in vitro

- for parasites and pathogens the environment is often the host (ex. a liver or a spleen)

Community

Collection of species occurring in the same place at the same time

Assemblage

assemblage of birds or ants

Guild

group of organisms that live in the same place and feed on the same resources

Infracommunity

all parasite species infecting a single host individual

Component community

all parasite species infecting a single host species or population in a given area

compound community

all parasite species infecting all host species in a given area

Ecology

why organisms are distributed the way they are

Abundance

number of individuals

Density

number of individuals per unit area of a species or population in a community

Parasitemia / infection density

Mean abundance of a parasite infection intensity is different within individual hosts

Measuring infection intensity/parasitemia:

Microscopy - just count em! (on body or under a microscope)

Quantitative PCR (pathogens) - PCR that every cycle of amplification takes a picture and measures florescence in your products

typically not all individuals in a host population are infected (infected/1 and uninfected/0)

binomial distribution

probability of "success" or infection: 1 or 0

assumptions:

1) hosts are independent samples from the population

2) each host has the same probability of infection

Prevalence

proportion of host individuals infected by a parasite

estimate of the probability of infection

variance

measure of spread of data around the mean

calculated as the average or the squared deviations from the mean

ratio of variance to the mean tells you about the distribution of parasites across host individuals

Poisson distribution

suggests random distribution of parasites among host individuals

Aggregated distribution

distributions of parasitemia (infection intensity) among host individuals where variance > mean

characteristic of macroparasite distributions

Negative binomial distribution

aggregated distributions are modeled using negative binomial distribution --> tells us the probability of a host having some number of parasites given

1) the mean number of parasites per use and

2) an aggregation of parameter k (aggregation parameter)

smaller k = more aggregated

bigger k = less aggregated (as 𝑘 → ∞ the distribution becomes Poisson)