Molecular that encode eight different proyeins i.e the Nucleocapsid

Characterization of and cluster analysis of Peste des Petits ruminants virus
strains circulating in Karamoja


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Peste des Petits
Ruminants (PPR) is a very highly contagious disease of small ruminants. PPR is
caused by an enveloped negative sense non-segmented RNA virus, Peste des Petits
Ruminants virus (PPRV). PPRV belongs to family Paramyxoviridae and genus morbillivirus
together with three other viruses; Rinderpest, measles and Canine distemper

The PPRV genome
is 15,948 nucleotides long and contains six genes (transacription units) that
encode eight different proyeins i.e the Nucleocapsid (N), Phosphoprotein (P),
Matrix protein (M), Fusion protein (F), Heamagglutinin protein (H) and two
nonstructural proteins C and V(Banyard et al., 2010). PPRV contains
host-derived envelope just like all the other members of the genus Morbillivirus and under the electron
microscopy, it is seen to contain a protein associated with genome, the
ribonuclear protein complex RNP. The assembly of the RNP, its association with
viral RNA, viral proteins and host factors remains a mystery(De Nardi et al., 2012).


PPR is endemic in
many of the developing countries globally and causes significant
socio-economical losses(Banyard et al., 2010). The disease is
spread around the world in most parts of Africa, Arabia, middle East and
southern Asia. In Uganda, PPR was first reported in Karamoja in 2007 (Abebe, 2016; Mulindwa et al., 2011). Antibodies against
PPRV had been detected much earlier than 2007 from sera samples from the
repository(Luka et al., 2012) implying that
the disease could have existed in East Africa many years before it was
confirmed probably because of miss-diagnosis due to the disease’s marked resemblance
with many other diseases that present with typical PPR clinical signs.


There is only
one PPRV serotype known and  there are
four distinct lineages of the PPR virus (I-IV) and in Uganda, three lineages
(I,II and IV) have been described  (Luka et al., 2012).Virulence seems
to vary from isolate to isolate much as there is only one PPRV serotype. This is
so because antibodies have been detected in animals without clinical disease
(or history)(Ecosystem & Kock, 2015; Mantip, 2013). PPR mortality
can go up to 50-80% depending on the isolate and host breed, susceptibility are
key factors as regards PPR mortality(Bailey et al,. 2005; Senthil Kumar et al., 2014). PPR control in
Uganda majorly relies on mass vaccination of the small ruminants. The vaccine currently
used requires cold chain and this is a problem because Uganda is largely a
third world country and there is little or no access to fridges/freezers. There
is a plant to employ a thermal stable PPR vaccine that throws some array of
hope of eradicating PPR at least by 2030 (Mariner, Gachanja, Tindih, & Toye, 2017). This study
will provide genetic data about the PPRV circulating in Karamoja and the neighbouring
Kenyan districts and also provide statistical data about to give an insight
about the spread patterns, source and possible hotspots and direction flow of
PPR spread, information that will contribute to the progress of PPR eradication



To characterize PPR
virus strains circulating in Karamoja and neighbouring Kenyan Districts


1.      To
determine seroprevance of PPR amongst small ruminants in Karamoja using
serological methods

2.      To
identify PPR lineages currently circulating in Karamoja and neighboring Kenyan
districts by gene sequencing and analysis

3.      To
determine the genetic relatedness of these viruses with isolates from the
neighbouring countries and the world over using Phylogenetic analysis tools

4.      To
predict PPR hotspots, directional flow of outbreaks using Geospatial mapping


Problem Statement

ruminant farming is the major source of subsistence and particularly, sheep and
goat provide the basic livelihood to the majority of Ugandan Peasants. PPR,
being a viral disease, is associated with high morbidity and mortality which is
a threat to food security and human basic needs. There is a strategic plan to
eradicate PPR using lessons learnt from the eradication of a related virus
(Rinderpest). However, there is not sufficient genetic information about the
PPR virus lineages responsible for the sporadic outbreaks of the disease in
Karamoja and the neighboring countries. Furthermore, there is limited
information about the vaccine strains and those responsible for the field PPR
outbreaks. It is also unclear where the source of the viruses responsible for
these outbreaks is from. With such knowledge gaps, it is very complicated to
successfully eradicate PPR.



poses a devastating threat to food security and socio-economic wellbeing of the
majority of the people in Uganda owing to its high morbidity and mortality
rates. Eradicating such a disease that has a grossly negative impact on the
people’s productivity is a key step towards successful execution of poverty
alleviation schemes. The information generated by this study will guide researchers
and other stakeholders on issues like the whether the vaccine covers all the virus
lineages circulating and therefore will help assess its ability to protect.
Geospatial mapping information will give an insight into how the disease moves
and which places are likely to have outbreaks. This is important especially
when the disease controllers know the source of infection such that they can
manage the disease better and ultimately eradicate it.





1.      What
is the seroprevalence of PPR amongst small ruminants in selected Karamoja

2.      What
PPR virus lineages are responsible for outbreaks in Karamoja and the
neighbouring Kenyan districts?

3.      Where
is the source of the PPR outbreaks in Karamoja?



Ø  Sample collection (type of sample,
transport media, conditions..)

Ø  RNA extraction

Ø  H c-ELISA (Biological Diagnostic
Supplies Ltd., Ayrshire, UK)

Ø  Real time RT-PCR screening

Ø  Conventional RT-PCR using PPRV N
gene primers

Ø  Amplicon purification and sequencing

Ø  Space and time cluster analysis
using  spatial scan
statistic for multinomial data technique