Biosciences  research  at    

Interna.onal  Livestock    

Research  Ins.tute  (ILRI)  A  seminar  given  by  Steve  Kemp  and  Vish  Nene  

at  University  of  Nairobi  5th  June  2013  

2  

3  

4  Source:  FAOSTAT,  2010  data  

Four  out  of  the  five  highest  value  global  commodi.es  are  livestock  

5  Source:  FAOSTAT,  2010  data  

%  growth  in  demand  for  livestock  products  2000  -­‐  2030  

6  

FAO,  2012  

ILRI  Mission  and  Strategy    

§  ILRI envisions a world where all people have access to enough food and livelihood options to fulfill their potential.

§  ILRI’s mission is to improve food and nutritional security and to reduce poverty in developing countries through research for efficient, safe and sustainable use of livestock— ensuring better lives through livestock

§  ILRI works in partnerships and alliances with other organizations, national and international, in livestock research, training and information. ILRI works in all tropical developing regions of Africa and Asia.

§  ILRI is a member of the CGIAR Consortium that conducts food and environmental research to help alleviate poverty and increase food security while protecting the natural resource base.

Strategic  objec.ves  §  ILRI  and  its  partners  will  develop,  test,  adapt  and  promote  science-­‐

based  prac%ces  that—being  sustainable  and  scalable—achieve  beXer  lives  through  livestock.  

Ø  ILRI  and  its  partners  will  provide  compelling  scien%fic  evidence  in  ways  that  persuade  decision-­‐makers—from  farms  to  boardrooms  and  parliaments—that  smarter  policies  and  bigger  livestock  investments  can  deliver  significant  socio-­‐economic,  health  and  environmental  dividends  to  both  poor  na.ons  and  households.  

Ø  ILRI  and  its  partners  will  work  to  increase  capacity  amongst  ILRI’s  key  stakeholders  and  the  ins.tute  itself  so  that  they  can  make  beXer  use  of  livestock  science  and  investments  for  beXer  lives  through  livestock.  

ILRI’s  competencies  

Integrated sciences Biosciences Gender and equity Vaccines

Resilience Genomics

Value chains and innovation Breeding

Zoonotics and food safety BecA

Feeds Genomics and gene delivery

Livestock and environment (both directions)

Feed biosciences

Policy, investment and trade Poultry genetics

Animal health delivery

Payment for ecosystem services

Conservation of indigenous animal genetic resources

Ruminants and monogastrics

ILRI’s  research  teams  

10  

Integrated sciences Biosciences

Animal science for sustainable productivity

BecA-ILRI hub

Food safety and zoonoses Vaccine platform

Livestock systems and the environment

Animal bioscience

Livelihoods, gender and impact Feed and forage bioscience

Policy, trade, value chains Bioscience facilities

ILRI  Resources  

•  Staff:  700.  

•  Budget:  $60  million.    

•  30+  scien.fic  disciplines.    

•  130  senior  scien.sts  from  39  countries.  

•  56%  of  interna.onally  recruited  

staff  are  from  22  developing  countries.  

•  34%  of  interna.onally  recruited  staff  

are  women.    

•  Large  campuses  in  Kenya  and  Ethiopia.    

•  70%  of  research  in  sub-­‐Saharan  Africa.  

ILRI  Offices  

Mali  

Nigeria  

Mozambique  

Kenya  

Ethiopia  

India  

Sri  Lanka  

China  

Laos  

Vietnam  

Thailand  

Nairobi: Headquarters Addis Ababa: principal campus In 2012, offices opened in: Kampala, Uganda Harare, Zimbabwe Office in Bamako, Mali relocated to Ouagadougou, Burkina Faso Dakar, Senegal

Biosciences  eastern  and  central  Africa  –  ILRI  Hub  

§ a  strategic  partnership  between  ILRI  and  NEPAD.  

§ a  biosciences  plahorm  that  makes  the  best  lab  facili.es  available  to  the  African  scien.fic  community.  

§ building  African  scien.fic  capacity.  

§ iden.fying  agricultural  solu.ons  based  on  modern  biotechnology.  

§ hosted  at  ILRI’s  headquarters,  Nairobi,  Kenya.    

 

§ Biosciences  infrastructure    

§ Biorepository    

•  Sampling is a very time-consuming and expensive exercise.

•  We have an ethical and scientific responsibility to make the best use of that effort and money!

§ Biorepository    

§ Sequencing  and  bioinforma.cs    

The Bioinformatics platform has 88 compute cores, 31TB of network-attached GlusterFS storage and back up systems.

• 454 GSFLX – 500 Mbases in 7 hour run – $10/Mb – 500bp read lengths – Homo-polymer problem

• Illumina MiSeq – 1.5-2Gbases in 27 hour run – $0.15/Mb – <150bp read lengths

§ Sequencing  and  bioinforma.cs    

§ Trypanosomias  research.  

§ Vaccine  research    

African Trypanosomiasis •  Caused by extracellular protozoan

parasites – Trypanosoma •  Transmitted between mammals by Tsetse

flies (Glossina sp.) •  Prevalent in 36 countries of sub-Sahara

Africa.

In cattle •  A chronic debilitating and fatal disease. •  A major constraint on livestock and

agricultural production in Africa. •  Costs US$ 1 billion annually. In human (Human Sleeping Sickness) •  Fatal •  60,000 people die every year •  Both wild and domestic animals are the

major reservoir of the parasites for human infection.

Trypanosomias  research  

Trypanosomes cause fatal disease in humans and livestock.

T. congolense,

T. vivax

T brucei rhodesiense T brucei gambiense

Control and Treatment of African Trypanosomiasis

Vector Control (Tsetse Fly) •  Using toxic insecticide •  Not sustainable •  Negative impacts on environment

Vaccine •  Tryps periodically change the major surface

antigen – variant surface glycoprotein (VSG) and evade the host immune system.

•  More than 2 decades, there is no effective vaccine developed.

Drug •  Drug toxicity and resistance •  Expensive

Bovins

Bovins et GlossinesGlossines

Cattle Tsetse Cattle and tsetse

Origins of N’Dama and Boran cattle

N’Dama Boran

Contribution of 10 genes from Boran and N’Dama

cattle to reduction in degree of trypanosomosis Boran (relatively susceptible)

The N’Dama and Boran each contribute trypanotolerance alleles at 5 of the 10 most significant QTL, indicating that a synthetic breed could

have even higher tolerance than the N’Dama.

N’Dama (tolerant)

-15-10-5051015

-15-10-5051015

Studying the tolerant/susceptible phenotype has problems:

•  Separating cause from effect

•  Separating relevant from irrelevant.

•  Dominance of the ‘what is happening to this weeks trendy gene/protein/cytokine?’ approach.

An EST Library screen identifies ARHGAP15282H->P mutation in the Bta2 (anaemia) QTL

Ø Screened EST libraries made from four

tissues from N’Dama and Boran for SNP within shortlisted genes.

N'Dama (n = 35) Boran (n = 28)282P-Allele 0.990 0.125282H-Allele 0.010 0.875

Gene frequency

H → P mutation at AA282

Alignment of N’Dama ARHGAP15 with homologues

Cow NDama KFITRRPSLKTLQEKGLIKDQIFGSPLHTLCEREKSTVPRFVKQCIEAVEK !

Cow Boran KFITRRPSLKTLQEKGLIKDQIFGSHLHTLCEREKSTVPRFVKQCIEAVEK !

Human KFISRRPSLKTLQEKGLIKDQIFGSHLHTVCEREHSTVPWFVKQCIEAVEK !

Pig KFITRRPSLKTLQEKGLIKDQIFGSHLHTVCERENSTVPRFVKQCIEAVEK !

Chicken KFISRRPSLKTLQEKGLIKDQIFGSHLHLVCEHENSTVPQFVRQCIKAVER !

Salmon KFISRRPSMKTLQEKGIIKDRVFGCHLLALCEREGTTVPKFVRQCVEAVEK !

ARHGAP15 is a RAC binding protein and the mutation at the proximal end of the RAC binding domain affects in vitro activity

The tolerant allele would be expected to inhibit RAC1 activity in the MAPK pathway which plays a key role in regulating inflammatory responses and could lead to the observed differences in expression or amplify downstream expression differences caused by other factors.

African Trypanosomes Infectivity

•  T. congolense

•  T. vivax

•  T. brucei brucei

•  T. brucei rhodesiense

T. brucei gambiense

Cattle Human Baboon (Papio papio)

+ - -

+ + -

Human and baboon resistance is due to innate Trypanosome Lytic Factor (TLF) in serum which is a subclass of high density lipoprotein (HDL) and can create pores in Tryps lysosome membrane and kill the trypanosomes by loss of osmoregulation.

- + -

Can we construct a transgenic cow with resistance to African Trypanosomiasis ?

•  Establish a transgenic cattle model with African Trypanosomiasis resistance using nuclear transfer (cloning).

•  On the background of a Kenyan indigenous breed – Kenyan

Boran. •  Introduce the gene – apoL-I from Baboon into Boran, which

is the key trypanolytic component of Baboon’s protective Trypanosome Lytic Factor (TLF) against both cattle and human-infective trypanosomes.

Complete  protec%on  from  human  infec%ve  Trypanosomes  by  baboon  apoL-­‐I  in    

transient  transgenic  mice  

0 20 40 60 80 100 120 140

0

20

40

60

80

100

Vector (N=6)

apoL-I + Hpr (N=5)

apoL-I (N=5)

**

Days post infection

• P  =  <  0.01  • Vector  vs.  treatment  

Thomson  et  al  PNAS  2009    106:19509-­‐19514    

Apol-3

Construct with Baboon ApoL-I Genomic

Sequence

Potential regulator

y Sequenc

e

Myh 9 (myosin heavy chain 9)

Chromosome 5 Cattle Apol Family Locus (6, 2 like, 4 like, 3)

Targeting Strategy

Apol-6, 2 like, 4 like

Project Strategy

Genomic locus of Baboon apoL-I gene

Vector construction

Validate the construct in transgenic mouse

Bovine embryonic fibroblasts (BEF) primary culture

Transfection & screening

apoL-I Transgenic BEFs

Nuclear Transfer

Transgenic calves

Phenotyping Trypanosome resistant transgenic Boran bull

ILRI

ILRI

Kenya Boran

Roslin Institute

New York University

Michigan State University

Nuc

lear

Tra

nsfe

r

(Clo

ning

)

Electrofusion

278 days

Bovine Embryonic fibroblast

Oocyte

Oocyte-cell couplet

Blastocyst

Cloned calf born

Enuclea.on  

Polar body

Polar body

Polar body

MII plate

UV+Transmitted light

Remove the PB and surrounding cytoplasm, as little as possible

Check removal of MII plate under UV light

Cell  Transfer  Fibroblast

Select the smallest, round cells with smooth and shining edge

Inject the selected fibroblast into the peri-vitelline space and push the cell in touch with the oocyte cytoplasm.

Oocyte-cell couplet

Electrofusion  

Line perpendicular to the electrodes

electrodes

Cell line: Kenya Boran, BEFs_E5_286, Male  

No. of Oocytes  No. of

Reconstructed Embryos  

No. of Blsts  

No. of Blsts transferred  

No. of Embryo Transfer  

Pregnancy   Abortion   No.  of  born  calves  

1244   723   85   22   16   5   3   2  

  58.1%   11.8%       31.3%   60.0%   40%  

Summary  of  Control  Nuclear  Transfer    

Name: Tatu Date of Birth: 16 July 2012 (Kapiti) Sex: Male Birth Weight: 46 kg Date of Death: 19 July 2012 (74 hrs) Cause of death: Low temperature, low blood glucose …

ID: CL001 (Tumaini) Date of Birth: 21 August 2012 (ILRI) Sex: Male Birth Weight: 35 kg Current age: 7.5 months, healthy

Two Cloned Calves born through Caesarean Section

At B

irth

6-

Mon

th

CL001 (Tumaini)

Identification of cloned calves with microsatellite markers

MS Marker ID   Chromosome  

Alleles Size    

E5 (Cell line)  

231-F (Tatu)  

BH058 (Mother)  

CL001 (Tumaini)  

Comment  

RM006   7  103.24   103.24     103.23  

Calf same as E5  106.96   106.95   106.88   106.93  

    110.7    

BM4440   2  

    123.69    

Calf same as E5 No allele as dam  

132.21   132.24     132.31  

136.54   136.55     136.57  

    143.41    

INRA053   7  90.96   90.92     90.86  

Calf same as E5  102.69   102.7   102.7   102.7  

    110.14    

BMS1116   7       141.67    

Calf same as E5  143.87   143.77     143.83  

146.03   145.93   145.96   145.96  

ILST098   2  

    93.02    

Calf same as E5 No allele as dam  

101.08   101     101.08  

104.77   104.73     104.79  

    110.45    

Two born calves are the same as the cell line in 11 microsatellite markers.

Future Activities

Transfection of Boran BEFs line (Roslin Institute, UK)

Establish Apol-I Transgenic Boran by Nuclear Transfer with Transgenic Cells

Phenotyping (confirm Tryps resistance)

•  Apol-I expression pattern

•  Killing of Trypanosomes in vitro (serum) and in vivo

(challenge)

•  Monitor the health conditions with growth

Increase Genetic Diversity •  Establish more transgenic cattle with

Kenya Boran BEFs lines

•  Establish transgenic cattle with other Kenyan indigenous breeds

Transgene Delivery •  Develop a breeding programme to

disseminate the transgene with farmers

Regulatory, legal, safety & public awareness issues

Future Activities

Tumaini A cloned Kenya Boran calf made by SCNT from a Boran embryo fibroblast cell line Cloned NOT transgenic

Current and future animal vaccine research activities at

ILRI Vaccine  Biosciences  

Interna.onal  Livestock  Research  Ins.tute  Seminar  at  CAVS,  Kabete  Campus,  5th  June  2013  

 

Importance  of  animal  health  research  in  the  developing  world  

Ø Livestock offer a powerful pathway out of poverty for ~750 million poor farmers in South Asia and Africa by providing nutritional and economic security.

Ø Infectious livestock diseases feature prominently among the constraints faced by livestock agriculture.

•  Endemic diseases •  Epidemic/pandemic diseases •  Trans-boundary diseases •  Emerging and re-emerging diseases •  Zoonotic diseases and food safety

Ø For many reasons diseases are neglected problems in affected countries, a situation exacerbated by a general lack of investment, vaccine R & D and manufacturing capacity.

List  of  current  ILRI  high  priority  diseases  targeted  for  control  

Ø African swine fever (ASF) – swine •  African disease threatens the global $150 billion/year pig industry

Ø Contagious bovine pleuropneumonia (CBPP) – cattle •  Regional losses to CBPP amount to ~ $60 million/year

Ø East Coast fever (ECF) – cattle •  Regional losses exceed $300 million/year; kills ~ 1million cattle/year

Ø Peste de petits ruminants (PPR) – small ruminants

•  Losses in Kenya alone amount to ~ $13 million/year

Ø Rift Valley Fever (RVF) – small ruminants, cattle and

human •  2006/7 outbreak in Kenya cost ~ $30 million

•  309 human cases in Kenya, Somalia and Tanzania; 140 deaths

Vaccines save lives and livestock and contribute to food security and poverty alleviation

Socio-­‐economic  impact  of  East  Coast  fever    in  sub-­‐Saharan  Africa  

 

Ø ECF present in 11 countries; it could spread to 8 more

Ø ~46 million cattle in region; ~28 million at risk

Ø ~1million deaths/year; losses > 300 $ million

Ø Small-holder farmers who would benefit: ~ 20 million

Theileria  parva    life  cycle    

R. appendiculatus

schizont-infected cells

sporozoites piroplasms

merogony

An  infec.on  and  treatment  vaccine  

A live vaccine for the control of ECF

(Muguga cocktail)

Problems: Liquid nitrogen cold chain, cost, immunological types

Immune  responses  that  contribute  to  immunity  

Anti-sporozoite

Anti-schizont

An.-­‐sporozoite  immunity:  p67  can  induce  immunity  to  ECF  

p67N

p67M

p67C

21 225

226 571

572 651

9 709

reduction in severe ECF by 50% in lab (25% immunity in field)

Average

A  classical  CD8+  cytotoxic  T  cell  response  to  the  schizont  stage  of  T.  parva  

CTL

P

CTL P

T cell receptor (TCR) on CTL recognizes parasite peptide associated with MHC class I molecules

Flowchart  of  CTL  an.gen  discovery  

ACTGGTACGTAGGGCATCGATCGACATGATAGAGCATATAGCATGACGATGCGATCGACAGTCGACAGCTGACAGCTGAGGGTGACACCAGCTGCCAGCTGGACCACCATTAGGACAGATGACCACACACAAATAGACGATTAGGACCAGATGAGCCACATTTTAGGAGGACACACACCA

Bioinformatics

tools

Predict ~ 5000 gene sequences & list candidate vaccine antigens

Clone genes of vaccine interest

Filter genes via immunological assays

T. parva genome sequence

A

Random cDNA library

B

Candidate CTL antigens

Map CTL epitopes

Mapped  parasite  CTL  an.gens/epitopes  

CTL epitope Peptide sequence MHC class I gene BoLA sero-type Tp1214-224 VGYPKVKEEML N*01301 A18 (HD6) Tp227-37 SHEELKKLGML T2b~ Tp249-59 KSSHGMGKVGK N*01201 A10 (T2a) Tp296-104 FAQSLVCVL T2c~ Tp298-106 QSLVCVLMK N*01201 A10 (T2a) Tp4328-336 TGASIQTTL N*00101 A10 (5.1) Tp587-95 SKADVIAKY T5~ Tp7206-214 EFISFPISL T7~ Tp8379-387 CGAELNHFL N*00101 A10 (5.1)

NetMHCpan  –  an  ar.ficial  neural  network  to  predict  CTL  an.gens/epitopes  

Center for Biological Sequence Analysis at the Technical University of Denmark

Incorporates correlated effects

Morten Nielsen

Use  of  pep.de-­‐MHC  tetramers  in  ECF  

CD

8+

Perforin+

Tp1+ cells

CTR

CTR

BB007

BB007

Diversity  of  BoLA  MHC  class  I  genes?  

Cattle - multiplex

RNA isolation from PBMCs

454 pyrosequencing

RT-PCR

Full length cDNA Exon 2- Exon 3

•  High throughput •  Rare variants Nicholas Svitek –

post-doc

Genotypic  diversity  –  a  hallmark  of  T.  parva,  can  compara.ve  genomics  help?  

Muguga, Marikebuni, Uganda ~ 64,000 SNPs

SNP distribution: ~ 65% exons, ~15% introns, ~ 20% inter-genic

81/4076 genes under positive selection (includes Tp2) [Henson et al., BMC Genomics 13: 503, 2012]

Joana da Silva – hybrid capture NGS

Sequencing more cattle and buffalo derived parasites

An.-­‐schizont  immunity:  trial  of  Tp  an.gens  

Graham et al., PNAS, 2006: 30% vaccinated cattle were immune to ECF

We  need  beXer  methods  to  generate  immune  responses  in  caXle  

Anti-sporozoite

Anti-schizont

Exploring vaccination systems

New adjuvants

Viral vectored systems

Old & new antigens

A  porholio  of  innova.on  and  vaccine  related  technology  plahorms  

Yeast&with&M.#myc&LC&genome&

(Delete&puta5ve&&virulence&factors)&

Less&virulent&M.#myc&LC&

ACTGGTACGTAGGGCATCGATCGACATGATAGAGCATATAGCATGACGATGCGATCGACAGTCGACAGCTGACAGCTGAGGGTGACACCAGCTGCCAGCTGGACCACCATTAGGACAGATGACCACACACAAATAGACGATTAGGACCAGATGAGCCACATTTTAGGAGGACACACACCA

Bioinformatics

tools

Predict gene sequences and list candidate vaccine antigens

Test experimental vaccine

Clone genes of vaccine interest (100’s of genes)

Filter genes via immunological assays

Pathogen genome mining (1000’s of genes)

Molecular immunology tools to assess immune responses in cattle

(10’s genes)

BASIC RESEARCH Increasing our knowledge base

“Knowledge lays the foundation for science”

§  Map immune responses to infection

§  Dissect pathogen biology & diversity

§  Study host-vector-pathogen interactions

§  Characterize pathogen virulence factors

§  Investigate the epidemiology of disease

§  Identify vaccine and diagnostic molecules

BASIC RESEARCH Increasing our knowledge base

“Knowledge lays the foundation for science”

§  Map immune responses to infection

§  Dissect pathogen biology & diversity

§  Study host-vector-pathogen interactions

§  Characterize pathogen virulence factors

§  Investigate the epidemiology of disease

§  Identify vaccine and diagnostic molecules

BASIC&RESEARCH&Increasing&our&knowledge&base&

&

“Knowledge*lays*the*founda2on*for*science”***

!

!  Map&immune&responses&to&infec>on&

!  Dissect&pathogen&biology&&&diversity&

!  Study&hostDvectorDpathogen&interac>ons&

!  Characterize&pathogen&virulence&factors&

!  Inves>gate&the&epidemiology&of&disease&

!  Iden>fy&vaccine&and&diagnos>c&molecules&

&&&&&&&&&&&!!

APPLIED&RESEARCH&Developing&new&

vaccines&&&diagnos>cs&&

“Vaccines*are*cost8effec2ve*an28disease*inven2ons”*

&

!  Assess&candidate&subunit&vaccines&

!  Assess&aHenuated&pathogen&vaccines&

!  Assess&different&vaccina>on&systems&

!  Engineer&thermoDstable&vaccine&formula>ons&

!  Develop&smarter&easier&to&use&diagnos>c&tests&

!  Facilitate&transla>on&of&outputs&to&products&

BASIC&RESEARCH&Increasing&our&knowledge&base&

&

“Knowledge*lays*the*founda2on*for*science”***

!

!  Map&immune&responses&to&infec>on&

!  Dissect&pathogen&biology&&&diversity&

!  Study&hostDvectorDpathogen&interac>ons&

!  Characterize&pathogen&virulence&factors&

!  Inves>gate&the&epidemiology&of&disease&

!  Iden>fy&vaccine&and&diagnos>c&molecules&

&&&&&&&&&&&!!

APPLIED&RESEARCH&Developing&new&

vaccines&&&diagnos>cs&&

“Vaccines*are*cost8effec2ve*an28disease*inven2ons”*

&

!  Assess&candidate&subunit&vaccines&

!  Assess&aHenuated&pathogen&vaccines&

!  Assess&different&vaccina>on&systems&

!  Engineer&thermoDstable&vaccine&formula>ons&

!  Develop&smarter&easier&to&use&diagnos>c&tests&

!  Facilitate&transla>on&of&outputs&to&products&

Acknowledgments  

Large number of past and current scientists at ILRI (Evans Taracha et al) and collaborators (LICR, Oxford Uni, Merial) Immuno-informatics approach:

John Barlow – University of Vermont Bill Golde – USDA-ARS (Plum Island) Soren Buus – University of Copenhagen Morten Nielsen - Technical University of Denmark

ILRI CRP funds TIGR and Craig Venter DFID NSF-BMFG (BREAD program) USAID – Feed the Future via USDA-ARS

The presentation has a Creative Commons licence. You are free to re-use or distribute this work, provided credit is given to ILRI.

ilri.org

Box 30709, Nairobi 00100, KenyaPhone: + 254 20 422 3000Fax: +254 20 422 3001Email: ILRI-Kenya@cgiar.org

Box 5689, Addis Ababa, EthiopiaPhone: +251 11 617 2000 Fax: +251 11 617 2001Email: ILRI-Ethiopia@cgiar.org

other offi cesChina • India • Mali Mozambique • Nigeria • TanzaniaThailand • Uganda • Vietnam

Better lives through livestockILRI is a member of the CGIAR Consortium

BeFer  lives  through  livestock  ilri.org

The presentation has a Creative Commons licence. You are free to re-use or distribute this work, provided credit is given to ILRI.

ilri.org

Box 30709, Nairobi 00100, KenyaPhone: + 254 20 422 3000Fax: +254 20 422 3001Email: ILRI-Kenya@cgiar.org

Box 5689, Addis Ababa, EthiopiaPhone: +251 11 617 2000 Fax: +251 11 617 2001Email: ILRI-Ethiopia@cgiar.org

other offi cesChina • India • Mali Mozambique • Nigeria • TanzaniaThailand • Uganda • Vietnam

Better lives through livestockILRI is a member of the CGIAR Consortium

BeFer  lives  through  livestock  ilri.org