1. Enter Sandman…
“The in vivo dynamics of antigenic
variation in Trypanosoma brucei”
Monica R. Mugnier, George A. M. Cross, F.
Nina Papavasiliou. Science 347: 6229, 2105.
1470-3
Joshua Gefen
2. Sleeping Sickness
[African Trypanosomiasis]
• A disease caused by a parasitic flagellate
protozoa of the species Trypanosoma brucei
• Infects both humans and animals (Nagana
disease)
3. • The transmission of the Trypanosoma brucei
between mammal hosts is usually by insect
vector – the Tsetse fly
5. Genome and Genetics
• 11 pairs of large chromosomes of 1 to 6
megabase.
• 3 to 5 intermediate chromosomes of 200-
500 kilobase.
• Around 100 mini-chromosomes of 50-100
kilobase. These may be presented as
multiple copies per haploid genome.
6. VSG Coating
[Variable Surface Glycoprotein]
• A conserved C-terminal
domain
• A variant and
highly changeable
N-terminal domain
7. VSG Characteristics
• Trypanosoma brucei populations can peak at a size of 1011
within a host, while ‘switching’ frequency is 0.1% per
division
• The switching of VSG can be identified as a stochastic
system – having a random probability distribution or
pattern.
• This rapid rate of switching is the basis of the constantly
diverse VSG population and the evasion of the protozoa
from detection by the immune system.
• The clinical effect of this cycle is a successive wave of
parasitaemia.
13. Trying to understand the pattern or the
hierarchy of VSG population as they expressed in
a host.
And now for the article…
“Despite attempts of modelling little is
known about the kinetic of VSG expression
during infection.”
18. Minor Problem
[Total population: 192]
“Although each infection initiated with a different
major VSG, the majority of variants (86%) appeared
in more than one infection, and nearly half (46%)
appeared in all four infections (Fig. 3C).” p. 1472
“Of the 48 VSGs that appeared in all four infections,
few were consistently dominant, and few were only
ever expressed as a minor variant (Fig. 3B).” p. 1472
20. Conclusion
• In their experiment, all the VSGs observed (65-
135 before day 30), may represent up to 35%
of the pre-existing repertoire. These
represent a lower-than-expected VSG
expressed diversity.
• The results show that VSG switching does not
occur at the “expected” rate – not enough for
immune evasion.
• Contrary to that, in-field observations and
samples indicated a higher-than expected VSG
diversity.
Numbers:
10,000 people per year contract the disease
60 million people live at risk of contracting the disease
Without treatment Sleeping Sickness is fatal.
In central & West African Sleeping Sickness is the second or the first cause of mortality (AHEAD OF HIV).
The mammal host gets bitten by the tsetse fly, which fills its blood sac, secretes the T.brucei on the skin – when the mammal scratches the insect wound, it basically inserts the parasite into the bloodstream.
The instant the agent gets to the bloodstream, it changes morphologically, as it moves from insect to mammal, over the course of one life-cycle
One notable change is the VSG [Variable Surface Glycoprotein] coating over its external membrane
The VSG enables escape from detection and destruction by the immune system
Most of the genes being expressed are helod on the large and intermediate chromosomes. When talking about VSG expression, the expressed genes of VSG are usually located in the subtelemarian area of the large chromosomes, while the mini-chromosomes hold only archive VSG genes (mainly pseudo-genes and silent genes).
************
[Antigenic variation in African trypanosomes displays a degree of order that is usually described as ‘semi-predictable’ but which has not been analysed in statistical detail. It has been proposed that, during switching, the variable antigen type (VAT) being inactivated can influence which VAT is subsequently activated. Antigenic variation proceeds by the differential activation of members of the large archive of distinct variable surface glycoprotein (VSG) genes.]
Now we’re going to dive into the VSGs, which are the topic of the presentation.
The VSGs are made of a highly conserved C-terminus anchor, attached to the protozoa membrane, and an N-terminal domain which dimerises to form a bundle of 4 alpha-helix. This part of the glycoprotein is very variable and can change between subspecies and different populations expressing different VSGs.
Because of the high density of the glycoprotein coating, the immune system really ‘sees’ only this layer and no other structures associated with the protozoa membrane. Hence, the VSGs would be the only antigen presented.
In order to get a glimpse of the mechanism and the dynamic of the VSG we should understand several aspects of it:
Def. ‘switching’: a change in the expression of a glycoprotein coat in one organism is a switching process.
These numbers can give you the estimates of how many switchings you can get in a host for a population of 1011.
A stochastic system is a random outcome of a probability-distribution pattern.
The rapid rate of switching and also the stochastic manner in which it expresses is the basis of the constantly diverse VSG population in a host, and the clinical phenotype of this effect would be a successive waves of parasetemia.
***
Density: The dense nature of VSG coating creates a physical barrier to the plasma membrane of the Trypanosoma brucei.
Variation:
These numbers assure that you can get much variety in the VSG population, in a host. Frequency of VSG ‘switching’: 0.1% per division: Show action’s increase.
The VSG coat undergoes frequent and stochastic, genetic modification, “switching” while using an archive VSG variants, allowing variant expressing of new VSG coat to escape the specific immune response raised against the previous coat.” In common with similar systems in other pathogens, the switching process is stochastic and spontaneous, and acts independently of antibody presence. It is also divergent and not simply progressional, as seen when a clonal first peak is followed by a first relapse peak that contains at least several VATs.
The repertoire of VSG variants is probably in a constant flux and differs among tripanosoma strains
Most mini-chromosomal VSGs appear functionally competent.
Subtelomeric regions are often underrepresented in genome sequences of eukaryotes. One of the best known examples of the use of telomere proximity for adaptive purposes are the bloodstream expression sites (BESs) of the African trypanosome Trypanosoma brucei
Subtelomeres are dynamic and fast-evolving regions of eukaryotic genomes owing to their remarkable plasticity. Recombination between internal repeats and chromosomal arms results in the accumulation of species-specific sequences, commonly mediating adaptation to the environment. Despite their extreme genetic diversity, common aspects of structure and function are shared across telomeres from a diverse range of organisms.
There are several mechanisms of VSG switching; we’ll go over them quickly. The expressed VSG is located in Bloodstream Expression Sites (BES), which are specialized subtelomeric transcription units. The total number of BES is dependant on the subspecies and strain, but is believed to be about 20 for the T.brucei Lister 427 Strain used in the present study.
ESAGs are found upstream of VSG genes in the BES. There are at least 6 different ESAGs in each of these Expression Sites. And each ESAG is repetitive in the genome. ESAGs are believed to reside only in VSG Expression Sites and to be cotranscribed with the VSG gene from a common promoter.
A 70bp repeat sequence is also found upstream to the VSG gene and is used in the different recombination mechanisms of switching.
(B) Mechanism of array VSG conversion: A silent VSG is copied from a subtelomeric VSG array into an ES, where it replaces the active VSG.
(C) Telomeric VSG conversion: a telomeric VSG (including 70bp repeat sequence upstream and telomere downstream) replaces the active VSG in the ES.
(D) Segmental VSG conversion: sequence is copied from a multiple inactive VSG genes and combined into novel mosaic VSG that occupies the ES.
(E) Transcriptional VSG switching: a non-recombination based mechanism that activates a new (previously silent) ES while inactivating the previously active ES.
They wanted to build a model to describe the hierarchy in which populations with different VSGs are expressed in a host. They want to open a question – if any – about a linkage between one kind of VSG and another.
Trying to understand the pattern or the hierarchy of VSG population as they expressed in a host.
Control Libraries: Control libraries were made using seven Lister427 clones each expressing a different VSG. These lines all had a marker at the promoter of the active expression site, and were grown in vitro in HMI-9 with antibiotic selection, to minimize in situ switching. Parasites were counted with a hemacytometer and mixed as indicated in Fig 1 and Fig S1. RNA was isolated and libraries were constructed using the VSG-seq library preparation protocol (below). [Control Libraries were made to validate the VSG-seq process.]
Infection and sample collection: Mice were infected with 5 pleiomorphic EATRO-1125 parasites. Parasitemia was counted every 2 days by hemacytometer. Every 3-4 days after parasitemia was collected, VSGs were measured by collecting blood. EATRO-1125 parasites originally express a specific VSG but in this experiment they constructed them and now they are heterogenous and each is expressing a distinct VSG. (The sum of protozeoa cells transmitted to the mice was about 20 – 20 specific VSG were expressed in the beginning of the experiment.) [Infection installation was done in order to check expression levels and dynamics of VSG ]
VSG-seq Library: Libraries were prepared from VSG PCR products. 100 bp single-end sequencing was performed. [VSG-seq library is a targeted RNA seq approach in order to assess the kinetics of VSG
* Mosaic and identification: Candidate Mosaics were identified by comparing VSG sequences to two independently assembled genomes for this strain. Candidate Mosaics were VSGs with less of 80% of their lining to any sequence in either genome and expressed in only one infection at a rate of less than 0.1% of the population.
A Control Experiment.
In order to validate the efficiency of the VSG-seq a control assay was performed, with 7 known VSGs.
(A) Efficiency of VSG assembly (mean ± SD). Control libraries made from a mixture of cell lines expressing different VSGs in known proportions were sequenced, and sequencing reads were assembled by using Trinity (13). Control mixtures were made from either 1 million or 10 million cells. (B) Quantification of VSG expression in control libraries (mean ± SD). The black bar (“Expected”) represents the proportion of cells expressing that VSG in the control mixture, and the gray bars represent quantification for each library by use of VSG-seq.
The x-axis measures time while the y-axis is the number of cells expressing specific VSG in 1ml of blood. What we can see in Fig. 2A, is the dynamics of expression of different VSG populations, in the first 30 days of progressional infection in the four mice. As we can see, there are fairly rapid cycles of expressions between the varied VSG populations. The sinusoid wave of one population is built from a dynamic within the host in which a VSG is becoming a major VSG (above 1% of the population), it is recognized by the immune system, and then it is suppressed (returns minor VSG, back to less than 1%).
Fig. 2B describes the late progress in the infection (only Mouse 3 survived), and we can see a more calm sinusoid wave, less variation, and a more statistically expressed VSG. We can assume that it is due to the exhaustion of the immune system.
Dynamics of VSG expression during early infection (days 6 to 30). Each colored line represents an individual VSG’s presence in the population, and the black line represents total parasitemia. Only variants present at >0.1% of the population at that time point are shown. When parasitemia could not be measured with a hemacytometer (<106/ml), parasitemia is artificially set at 105/ml in order to allow for visualization of the population. Because there are so many VSGs expressed during infection, colors are difficult to distinguish; overall, variants do not reappear later in the same infection. A smooth curve connects points at which expression or parasitemia was measured; these curves are for visualization and do not imply the actual kinetics of variant expression between points. This figure is representative of four infection experiments (mouse 2 is shown). (B) Dynamics of VSG expression during late infection (days 96 to 105) for mouse 3. (C) Number of VSGs present at each time point. Any variants quantified as >0.01% of the population are included.
* Also a great diversity, even within parasetemic valleys. VSG-seq identified an average of 28 variants at each time point.
Fig. 3A: the x-axis describes the days post-infection while the y-axis describes the count of different minor variant VSGs (and when I say minor, I mean a population less than 1%) We can see that after day 30, there is an increase in the diversity of the minor population.
In order to see if this infection shows any bias or hierarchy, in the VSG expression, the researchers compared the repertoires of all 4 mice. This is presented in Venn diagram.
Variant emergence during infection.(A) Minor variants present at each time point (mean ± SD). A minor variant is arbitrarily defined as any VSG that never exceeds 1% of the population during the course of infection in a single mouse. Major variants are any variant that exceeds 1% of the population at some point during infection. (B) Venn diagram comparing the fates of VSGs appearing in all four infections. (C) Intersection of sets of VSGs expressed during early infection (days 6 to 30). The total number of VSGs is listed in parentheses below the mouse number. (D) Venn diagrams showing intersection of VSGs expressed early in infection (VSGs from mouse 1, 2, or 4 versus VSGs from mouse 3, days 7 to 30) and intersection of VSGs expressed early in infection with VSGs expressed late in infection (VSGs from mouse 1, 2, or 4 versus VSGs from mouse 3, days 96 to 105).
PROBLEM:
The last assay the researchers did was identifying mosaic VSGs. A segment-gene conversion event which generates mosaic VSGs was observed and was not previously encoded in the genome. It is unknown whether mosaic VSGs form at the active expression site or within the silent repertoire before expression (archive VSGs). To test that these were true mosaics and to determine when they were formed, the researches used VSG specific primers to confirm their absence from the parental strain and present within genomic DNA. They identified three mosaics. All of them need a PCR amplification in order to be noticed. Their amount in vivo is very minor. The mosaic formation is a mechanism for increasing repertoire diversity in the late infection.
Mosaic VSGs can be identified throughout infection.(A) Transient expression of a mosaic VSG in the population. PCR confirmation of the mosaic is shown below. The black line represents total parasitemia at each day after infection, and the green line represents the number of parasites expressing the mosaic VSG. “n.q.” indicates that the VSG is detectable within the population, but not quantifiable. “n.d.” indicates that the VSG is not detectable within the population. Below the graph are products from PCR of gDNA at each time point, by using either primers specific for the mosaic VSG or the control gene, ura3. This VSG could not be amplified when first detected with VSG-seq, likely because of low cell numbers in the DNA sample (probably less than 10 cells). (B) Mosaic from late infection, with PCR confirmation of the mosaic shown below.
The results show that VSG switching does not occur at a rate that would be expected as a sufficient rate for immune evasion. With only few variants present at any time.
A recombinatorial mechanism can explain the expansion of pre existing VSG repertoire. This may be critical in long term infection.”
Samples that were collected from Sleeping Sickness patients show higher than expected VSG diversity.
This research can provide a foundation for the study of VSG switching and diversification in vivo.