cpgr executive summary 2010

8/6/2019 CPGR Executive Summary 2010

1/16

Executive Summary


2/16


3/16

2 | P a g e Registered office: IIDMM, S2.09 Wernher Beit South Building, Anzio Road, Observatory, Cape Town 7925, South AfricaIncorporated in South Africa under section 21, registration number 2006/010411/08

Key features of the CPGR

Leading cross-sector, multi-disciplinary omics platform in Africa; State-of-the-art Genomics facility utilizing Affymetrix, DNA array and qRT-PCR workstations; State-of-the-art Proteomics facility based on multiplex protein arrays, bead arrays and MALDI-

ToF/ToF technology platforms;

Proven track record of delivery, having completing more than 200 omics projects for south Africanand international clients (2007-2010);

Flexibility to work with academia and industry in fields such as drug development, biomarkers andmolecular crop marker development;

More than 50 validated genomic and proteomic workflows (e.g. RNA expression profiling, ms-basedbiomarker discovery, multiplex biomarker assays on Luminex platform);

ISO/G(C)LP quality management system designed to meet customer requirements in academia andindustry in a flexible fashion;

Core Bioinformatics capacity to facilitate efficient analysis and interpretation of microarray,sequencing and mass spectrometry data;

Leading know-how in culturing and handling HepaRG liver cells for toxicology assessment of drugcompounds;

Workflows for recombinant expression of proteins in insect cells, and other host systems, for theexpression of proteins for assay development.


4/16


Content

What is the CPGR? What is the purpose of the CPGR How does the CPGR work? What are the benefits of working with the CPGR? Overview of Genomics, Proteomics and Bioinformatics in modern biotechnology


5/16


What is the CPGR?

The CPGR is a multi-disciplinary biotech platform, legally established in South Africa as a not-for-profit

organization. The organization, based in Cape Town, South Africa, combines state-of-the-art information rich

genomic and proteomic (omics) technologies with bio-computational pipelines to create novel and custom

solutions for biological and

biomedical problems in the human

health and the agri-biotech sectors.

A multi-disciplinary team of

technology application specialists,

scientific project managers and bio-

informatics experts works in a

customer-centric manner to generate

value for clients in academia and

industry.

The CPGR is housed in laboratories

within the Institute of Infectious

Disease and Molecular Medicine (IIDMM), University of Cape Town, and is equipped for high end mass

spectrometry (ABI 4800 MALDI TOF/TOF), 2D nano-LC (Dionex), DNA/protein microarraying (Genetix

QArray2), high density gene chip analysis (Affymetrix GS3000 system), microarray scanning (Tecan LS), real-

time RT-PCR (ABI 7900), and DNA/RNA analysis (Agilent 2100 bioanalyser), amongst others. A highly skilled

laboratory staff compliment maintain and run these key pieces of equipment, while providing critical

support in services and projects for members of the scientific community.

The CPGR provides project support in a diverse range of fields which include lifestyle diseases such as

diabetes and cancer, infectious diseases such as TB and HIV, and molecular crop development in plants such

as maize and grapevine. The organization can handle samples and isolates from most biological sources,

including human, animal, plant, yeast, bacteria and virus in a secure Biohazard Class II (BSL II) environment.

To create effective solutions in complex biological projects, the CPGR has established more than 50 validated

genomic, proteomic and bio-informatic workflows. These include array-based RNA expression profiling on an

Affymetrix GeneChip platform, mass spectrometry based protein ID and biomarker discovery on an ABI 4800

MALDI-ToF/ToF, and multiplex antibody capturing assays on a protein array. Computational workflows for

high-throughput analysis of genomic and proteomic data-sets, including standard DNA and next-gen

sequencing data complete the portfolio.

Sample

DNA

Chromatin Methylation

Genoytping

CNV/LOH

Promoter-analysis

Sequencing

RNA

miRNA

Protein

Gene expression

Exon expression

miRNA expression

Protein expression

Protein ID

Protein sequence

DATA


6/16


The CPGR has incorporated world-leading know-how in culturing and handling HepaRG liver cells for

toxicology assessment of drug compounds into an integrated workflow putting the power of its omics

platforms to an enhanced, value-creating use. The CPGR places a strong emphasis on developing and

offering unique solutions in a

systems-based manner in

drug development and

disease biomarker discovery

programs.

The organization has

implemented a unique quality

management program which

incorporates elements of

ISO17025 and G(C)LP to

create a system that meets

the flexibility required for

basic research projects but

provides the consistency and

compliance required in a regulatory environment. Quality gates are integral to workflow development andexecution and ensure that only data of the highest quality are generated and released.

The organization is building significant bio-informatics capacity to support its integrated omics laboratory

as well as the growing demand for the interpretation of data generated in other information-rich analytical

platforms. The approach integrates the design of omics studies that utilise genomic and proteomic

analytical platforms with informatics for mass-data analysis, treating each component as an equal and

necessary component to create turn-key solutions for complex biological problems.

Currently, the CPGR does not have its own core research budget. Rather the organization actively seeks to

establish collaborations with leading biomedical and plant researchers and academics in South Africa and

abroad. The goal is to stimulate new translational research programs supported by the CPGRs equipment

and expertise.

Concurrently, the CPGR actively pursues business development and marketing strategies that put its offering

into the context of the international biotech and pharmaceutical markets; the strategy aims create value in

highly dynamic sector, and inevitably to apply this ability to support the creation of a thriving bio-economy

in South Africa.

Bioinformatics

Cell culture

assaysRecombinant

protein expression

Genomics ProteomicsTranscriptomics

Systems Biology

Validation

Translation


7/16


What is the purpose of the CPGR?

The CPGR is based on an initiative by the South African Department of Science and Technology (DST)

through its funding vehicle the Technology Innovation Agency (TIA) whose purpose is to create a more

powerful biotech innovation system and to grow an internationally competitive bio-economy in South Africa.

The organization was initially funded by the Cape Biotech Trust (CBT) and PlantBio (PB) in 2006; both

organizations have since been incorporated into the Technology Innovation Agency (TIA). Amongst its

membership the CPGR features some of the most prominent tertiary institutions in South Africa, such as

University of Cape Town (UCT) and University of Stellenbosch (US), and renowned international

organizations (FIND, Foundation for Innovative New Diagnostics).

The CPGR was established to

address a critical gap in the

innovation continuum in the

biotech sector in South Africa;

the gap is a lack of

infrastructure, capacity and a

track record in the fields of

Genomics and Proteomics. The

primary purpose of the

organization is to create, retain

and attract value in South

Africa for the benefit of a

growing bio-economy. This

value can be measured by the increase in the number and quality of publications, patents registered, human

resources retained in the system, biological samples analyzed in South Africa, business opportunities created

by the CPGR, funding attracted, or investments made in the sector by private and public entities.


8/16


How does the CPGR work?

The CPGR is a hybrid social enterprise; it combines a strong public benefit mandate, supporting academic

research, with a value-generating service model for the industrial biotech community. In essence the CPGR

creates and provides specialist knowledge, support, data and products to clients in academia and industry,

with relevance to their processes, projects or businesses.

Currently, the CPGR combines elements of the following biotech business models:

Platform model: a series of state-of-the-art genomic and proteomic technologies are employed tocreate novel and improve existing workflows to achieve incremental improvements in clients R&D

processes and projects. Contract research model: A diverse array of platforms, technologies, workflows and expertise is

utilized to create integrated solutions and to generate research results for clients and with

collaborators.

Open source model: A strong focus on training and skills development is employed to create a baseof empowered omics scientists in South Africa.

After submitting a request, clients are guided through a structured project preparation and study design

process aimed at formulating scientific questions that best utilize the available resources (biological samples,

scientific

expertise,

technologies

and workflows)

in an effective,

solution driven

manner. This is

followed by theexecution of a project, using a project plan, and typically involving a series of quality-controlled experimental

procedures. At the end the analysis, a dataset and an analytical report are generated. Data can then be

subjected to further custom analysis using the CPGRs internal bio-computational pipelines for clustering,

assembly, annotation or visualization. The process and interaction with the client is designed such that

maximum value can be created from biological samples and research questions.

Bio-consulting

Bio-analysis

Bio-Informatics

RequestConsul

tation

Studyplan

Service /Project

ReportData

analysisData-

mining


9/16


What are the benefits of working with the CPGR?

It is widely acknowledged that omics disciplines, in combination with bio-informatic support have the

potential to provide solutions to some of humankinds most pressing problems. Potential applications

include identifying new drug targets, finding new biomarkers for the treatment of diseases and developing

better crops. However, because of the complexity underlying some of the fundamental biological problems

in these areas, it is crucial that omics technologies are applied in the most effective manner possible to

leverage the full benefit of these disciplines.

The CPGR applies omics technologies in the following manner:

Common problems CPGR

Poor quality data, in particular inthe less mature technologies (e.g.

Mass Spectrometry)

Rigorous validation of workflows; stringent QA/QC systems includingquality gates in workflows; proficiency testing; and inter laboratory

comparisons

Disconnect of data-generation and

data-analysis

Strong links between data generating platforms and computational

biology; a multi-disciplinary team of experts can assist with design,

execution, and analysis of omics projects in one place

Disconnect of biology and omics In-depth understanding and handling of biological systems, omics

technologies and bio-computational solutions in one place enhances

value generation and the innovation potential in R&D programs

Value chain thinking, sequentialproblem tackling, engineering

fallacy

Value systems approach: iterative, adaptive, learning- and solutions-focused strategies

More data than questions to ask Solutions designed to generate problem-specific outputs

Study plan

Sample(s)

Experiment

Raw data

Study statistics

Sample mgmt

Data mgmt

Data analysis

WET DRY


10/16


An overview of Genomics, Proteomics and Bioinformatics in Modern Biotechnology

Modern biotechnology, as opposed to traditional biotechnology, is commonly viewed as originating in the

development of recombinant DNA technologies in the early 1970s. Following from this a series of radicalscientific and technological innovations have changed the sector, leading to achievements such as the

sequencing of the complete human genome, the development of stem cell technology and the discovery of

RNA interference. The key technologies used in modern biotechnology are highlighted in the table below

together with the CPGRs service offering.

Technology Examples CPGR

Nucleic Acid (DNA-

RNA) related

technologies

High throughput sequencing ofgenomics, genes DNA

Genetic engineering Antisense technology siRNA technology

Affymetrix GS3000 genechip system DNA Arrays qRT PCR (ABI7900)

Protein-related

technologies

High Throughput Protein/Peptideidentification, qunatitation and

sequencing

Protein/Peptide Synthesis Protein engineering and

Biocatalysis

MAKDI ToF/ToF HPLC Protein Extraction

Metabolite Related

Technologies High throughput metabolite

identification and quantification

Metabolic pathway engineering

Cellular/Sub-cellular

related technologies

Cell hybridisation/fusion Tissue engineering Embryo technology Gene delivery Fermentation and downstream

processing

Cell culture assays (cell Lines) Recombinant protein expression in

insect cells

Supporting tools Bioinformatics Comprehensive bioinformatics services


11/16


The 21st

century is set to witness the growing impact of modern biotechnology as a major contributor to the

sustainable development of the world. Insights into biological phenomena through advancements in

genomics, proteomics, bioinformatics and other "omics" disciplines are accelerating at an impressive rate.

The tools employed in these information-rich areas of science provide new opportunities for drug and

diagnostic development, crop production, food sciences and bio-safety. The graph below depicts the

dramatic rise in scientific activity in the areas of genomics, proteomics and bioinformatics.

Genomics

Genomics refers to the systematic study of the relationship between structure and biological function of all

genes in an organism. More specifically, Genomics is the study of the genetic information contained in a

single cell, organ, tissue or whole organism on a system-wide and systematic scale. Today, the term is also

used to describe the analysis of the full complement of coding and non-coding RNAs in a given biological

system (also called Transcriptomics).

Development in the field of Genomics was spurred by two innovations in the recent history of modern

biotechnology: firstly, the invention of Polymerase Chain Reaction (PCR) in 1983 and secondly, the

development and optimization of DNA sequencing in the 1990s. These led to the complete decoding of the

human genome in 2001. Most importantly, the information garnered from high-throughput sequencing and

other information-rich genomic applications provided the raw data for the exploding field of bioinformatics,

where computer science and biology join forces to explore the unchartered realms of biotech innovation.

Omics-relevant citations p.a. in PubMed vs HIV

14000

12000

10000

8000

6000

4000

2000

0

No.

ofcitations

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

Genomics

Proteomics

HIV

Bioinformatics

The terms Proteomics,

Genomics and

Bioinformatics were

used to search the

PubMed

(http://www.ncbi.nlm.nih.gov/pubmed/) for

publications in 1985 to

2008. The term HIV

was used to serve as a

reference. The search

was done on 23rd

November 2009.
http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/http://www.ncbi.nlm.nih.gov/pubmed/


12/16


The impact of Genomics on the fields of life sciences and biotechnology is manifold. It has been shown that

Genomics can

Accelerate the identification of novel drug targets in genome-wide association studies (drug targetdiscovery and validation);

Facilitate the identification of drug-risk profiles in early preclinical development, therefore helping toimplement better go/no-go gates (Toxicogenomics);

Enhance the stratification of patients enrolled in late-stage drug development, therefore reducingthe costs of clinical trials (Pharmacogenomics);

Stimulate the development of novel multivariate signature assays, paving the way for improvedMolecular Diagnostics tests and Personalized Medicine;

Support the identification of quantitative traits underlying the more efficient moleculardevelopment of higher-yield crops (Molecular Crop Breeding).

Proteomics

Proteomics is defined as the global study of proteins, including the investigation of their structure,

expression and inter-action on a system-wide scale. Proteomics technologies are set to play a key role in

information-rich discovery approaches in the post-Genomics era. Based on the advances that have been

made in the field of mass spectrometry (MS) in particular, MS-based biomarker discovery is set to play an

increasingly critical role in diagnostics and drug development. As awareness of the benefits of the available

technologies grows, high-quality services will become an issue for public research institutions such as

Universities.

In the last decade the number of proteomic-focused projects funded by the United States National Institute

of Health (NIH) has increased significantly In 2000, 52 such projects were funded; by 2003 this had grown to

970 projects. According to the analysis of an NIH database, by fiscal year 2009 the NIH had awarded, $356.5

million in grants for proteomics research, including nearly $55 million in stimulus funding. In total, 1,026

proteomics grants were awarded in 2009, averaging $347,468 per grant. This increase in proteomic related

research is reflected by the success of companies focused on protein technologies and companies applying

the corresponding tools to enhance internal R&D efforts.

In line with a steep increase in grant funding, a rapid evolution of Proteomics technologies, and a rapidly

increasing interest in tackling biological questions at the protein level, researchers playing in this field face a

range of challenges, including:

The need for the analysis of complex biological mixtures; The ability to quantify separated protein species;


13/16


Insufficient sensitivity for proteins of low abundance ; The quantification over a wide dynamic range; The ability to analyze protein complexes; High throughput / high reliability of workflows and applications; Robust, routine applications.

Based on recent technological developments, proteomic technologies are expected to play a significant role

in:

Drug discovery & development: The high failure rate of potential drugs is driving research on theidentification of protein biomarkers that are likely to act as surrogate primary end points in clinical

trials for predicting drug efficacy in animals and humans. Proteomics has the potential to reduce

drug development time and drug attrition rates. If total development time is reduced by three years

and the number of successful New Drug Applications (NDAs) doubled, R&D costs could be cut by as

much as 30% per year;

Early disease management: The early detection and diagnosis of fatal and degenerative diseases particularly cancer, Alzheimers, cardio vascular disease and diabetes improves prognosis,

management and cure. The development of tests with the highest sensitivity, specificity and

predictive power is a major goal for science;

Improved diagnosis & prognosis: Developing diagnostic and screening tests that employ multipleprotein biomarkers rather than relying on tests with a single marker will improve diagnosis and

prognosis;

Personalized & predictive medicine: Biomarker-based screening tests will help to predict deadlydiseases in the early stages and these tests are likely to help physicians in prescribing personalized

medications. This will lead to reduction in side-effects and ensure that patients are administered the

right medication.

In general, a shift in focus from discovering genomic biomarkers to protein biomarkers is driving demand for

robust research instruments that enable multiplexing and reduce manual steps such as sample preparation.

In turn, this will put increasing pressure on core facilities to keep abreast with the latest developments to

ensure that maximum value can be extracted from biological samples in projects aiming at crop

improvement, drug discovery or diagnostic test development. The main bottleneck in proteomics is the

ability to analyze the vast amount of data generated, it is essential for organisations to invest heavily in

bioinformatics.


14/16


Bioinformatics

Bioinformatics is the application of information technology to the field of molecular biology. Its primary use

since the late 1980s has been in genomics and genetics, particularly in those areas of genomics involving

large-scale DNA sequencing. Bioinformatics now entails the creation and advancement of databases,

algorithms, computational and statistical techniques, and theory to solve formal and practical problems

arising from the management and analysis of biological data.

The primary goal of bioinformatics is to increase our understanding of biological processes. What sets it

apart from other approaches, however, is its focus on developing and applying computationally intensive

techniques (e.g. pattern recognition, data mining, machine learning algorithms, and visualization) to achieve

this goal. Major research efforts in the field include sequence alignment, gene finding, genome assembly,

protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein

interactions, genome-wide association studies and the modeling of evolution.

In essence, Bioinformatics today is characterized by 4 major components:

1) IT-support to more efficiently create, manage and store biological data generated on information-rich omics platforms;

2) Development and implementation of tools (pipelines) that help create high -quality raw data in arobust, repeatable manner;

3)

Development, implementation and management of bio-computational tools that enhance theextraction of biologically meaningful information from raw data and that facilitate the interpretation

of results (visualization);

4) Integration of data generated on different technology platforms and/or various levels of biologicalcomplexity (DNA, RNA ,protein, etc) to enable a systems-based, in-silico representation of biological

phenomena.


15/16


16/16

Contact

Centre for Proteomic & Genomic Research

Institute of Infectious Disease & Molecular Medicine (IIDMM)

S2.09 Wernher Beit South Building

Anzio Road, Observatory

Cape Town 7925

South Africa

Tel: +27 21 406 6126

Fax: +27 21 404 7657

[email protected]

www.cpgr.org.za

cpgr executive summary 2010

Documents