Parasite genomics Flashcards

(38 cards)

1
Q

Prokaryotic genome description (4)

A

1) Nearly all coding (no-nonsense)
2) Few repetitive
3) Rapid evolve
4) Large population sizes

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2
Q

Eukaryotic genome description

A

1) Lots of noncoding
2) Lots repetitive element
3) Conserved mode of evolution
4) Smaller population sizes

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3
Q

Prokaryotic genome shape

A

-circular
-plasmids

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4
Q

Eukaryotic genome shape

A

linear chromosomes

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5
Q

Parasite genome description

A

-Larger genome
-different arrangements and structures
-low abundance
-complex life cycles and host interactions

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6
Q

What processes lag when it comes to treating parasites

A

-prioritisation methods
-pipeline development
-applications of public health

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7
Q

what does toxoplasma gondii cause

A

Toxoplasmosis

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8
Q

What does severe toxoplasmosis cause

A

-brain and eye damage

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9
Q

What does congenital toxoplasmosis cause

A

-miscarriage/still birth
-hydrocephaly
-microcephaly
-brain/eye damage later

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10
Q

What protein is most abundant on toxoplasma gondii

A

SAG1 on cell surface

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11
Q

What gene plays a major role in reducing Toxoplasma gondii

A

-1 gene
-SRS29C

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12
Q

What is lymphatic filariasis

A

-neglected tropical disease
-causes damage to lymphatic system
-mosquito borne
-Eosinophillia

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13
Q

What damage does lymphatic filariasis cause

A

-lymphedema
-bacterial infections of skin and lymph
-hardening and thickening of skin

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14
Q

What is Elephantiasis

A

hardening and thickening of skin

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15
Q

Novel lymphatic filariasis treatment discovery

A

-genome of Brugia Malayi explored
-essential metabolic enzymes identified
-compared with US FDA approved

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16
Q

What is VEuPathDB

A

-14 databases
-over 709 organisms
-can be non-pathogenic and host

17
Q

what is cryptosporidium

A

an apicomplexan gastro-intestinal protozoan parasite

18
Q

Treatments for cryptosporidium

A

-none in EU and UK
-US = Nitazoxanide

19
Q

Acute cryptosporidiosis in UK

A

-especially common in young children
-8 cases for every case reported
-multiple outbreaks a year

20
Q

Diagnosing cryptosporidium

A

-ICLF dipstick
-Ziehl-Neesen stained microscopy
-Auramine phenol stained microscopy
-Enzyme immune assay
-PCR

21
Q

How to improve cryptosporidium treatments

A

-better detection
-identify; mechanisms, new target sites, virulence factors, clinical impact

22
Q

Cryptosporidium genome factors

A

-8 chromosomes
-highly compact coding genes (75%)
-AT rich
-Introns in 11% genes
-low complexity
-high repeats

23
Q

How is sample prep for cryptosporidium challenging

A

-oocytes shed into faeces
-may be low density
-hard to isolate from background material
-DNA extraction could cause dilution

24
Q

DNA mix in a faecal sample from someone with cryptosporidium

A

-Host DNA with small % cryptosporidium

25
Pre-extraction process for high quality DNA
1)oocytes harvested by flotation (semi purified) 2)concentrated and purified by IMS 3)oocytes sterilised by 0.6% NaClO
26
how can genome be amplified
Multiple displacement amplification (MDA)
27
benefits of using multiple displacement amplification
-no need for IMS -extends sample to be analysed
28
genomic diversity of a parasite population was shown how
-Tests of children in Bangladesh -aliquots of fecal material from same child showed genomic diversity -high recombination rates
29
where does C. Hominis infect
almost exclusively low-middle income countries
30
where does C. Aquapotensis infect
high-income countries with improved sanitation
31
how is gp60 gene useful
-hypervariable for diversity -shows different types of cryptosporidium
32
what was the initial focus for Multilocus Genotyping (MLG) scheme
C. Parvum
33
advantages of fragment sizing to identify tandem repeats (C. Parvum)
-cost effective -rapid automated -samples can contain >1 allele -indicate how often multiple infections occur
34
MVLA subtyping scheme for C. Parvum
7 locus subtypes
35
Subtype of C. Parvum in December 2020
gp60 subtype llaA16G1R1 MVLA profile 4-14-5-7-18-25-17
36
common MVLA in animal contact outbreaks
gp60 = IIaA17G2R1
37
What does MVLA help to identify
-indicate unrecognised outbreaks or cases missed by surveillance alone
38