Different omic technologies were traditionally developed by separate industries. These worlds will have to come together to seize opportunities in multi-omic sample preparation, assay design or instrument development to accelerate biological and pharmaceutical discovery, says TTP’s Lauren Laing.

High-throughput technologies that provide detailed read-outs of individual “omes” – such as RNA-seq for the transcriptome and mass spectrometry for the proteome – are revolutionising our understanding of all aspects of biology, from the inner workings of human cells to disease progression.

But no matter how well we understand a single ome, it can only provide a limited perspective on cellular activities.

Enter the burgeoning field of multi-omics, which aims to integrate our understanding of the diverse components of cellular life in ways that haven’t been achieved before.

To do so, multi-omics combines information from an increasing number of omes, including the genome, epigenome, transcriptome, proteome and metabolome, to provide deeper insights into the complex molecular hierarchy at play in countless biological systems and settings.

The information gleaned from these complete ome combinations will be vital to unlocking the previously hidden world of how genetic mutations or epigenetic changes can influence gene expression or protein levels (and back again).

But combining these worlds presents challenges.

Diverse technologies to measure different omes were developed by largely separate industries with specialised expertise and historically limited cross-pollination. Designing novel multi-omic assays or platforms from the ground up would require engineers, optical physicists, mass spectrometry or microfluidics experts, alongside biochemists.

These areas of expertise are often lacking in-house in companies dedicated to a single omic discipline, so experts must now come together to establish multi-disciplinary industrial partnerships to solve key challenges before true “ome-wide” multi-omics approaches are possible.

We discuss the current state of the industry, who will likely benefit the most from multi-omics, and the key challenges and opportunities for technological innovation.

Drug discovery: An unprecedented view through the multi-omics lens

The single-cell multi-omics market alone is estimated to reach nearly 9 billion US dollars by 2030 and has the potential to profoundly transform drug discovery on the way.

In drug discovery, before commencing a therapeutic screen, a prior deeper understanding of the different layers of disease progression would give a clearer idea of which part of a disease pathway it is possible or most effective to target with a small molecule library.

Multi-omics enables a more informed decision on whether to target the genome directly, inhibit transcription, encourage mRNA degradation or aggregate problematic proteins, potentially reducing the lead time of therapeutic compounds to the clinic by accurately identifying drug targets, decreasing the failure rate and saving money.

Ultimately, multi-omics could be a game changer for pharmaceutical companies’ crucial decision points in therapeutic development. Still, the industry must overcome some key hurdles before multiple omes are simultaneously profiled in their entirety.

The state of omics today

Each omics industry has made impressive progress in recent years.

Diligent technological development and continual innovation have propelled next-generation sequencing (NGS) genomics, epigenomics and transcriptomics technologies into an ultra-scalable and affordable domain to drive routine use in standard research and development workflows.

Similarly, in the parallel world of high-throughput proteomics, improved integration and automation of mass spectrometry approaches have effectively increased throughput to a level only slightly lower than genomics and transcriptomics. This now enables its use in large-scale therapeutic discovery studies and clinical trials.

Likewise, we are seeing a wave of Next Generation Proteomics technologies build larger and larger panels utilising for example aptamer or antibody technologies in concert with qPCR or NGS readouts, thereby improving the accessibility of proteomics readouts to established genomics facilities.

Because of these increases in throughput and accessibility, in recent years, the two market segments are beginning to communicate. This cross-pollination has accelerated exciting technological advancements where read-outs of whole genomes or transcriptomes are combined with more limited proteomic read-outs for a handful of proteins simultaneously. Adding the ability to interrogate samples at single-cell resolution extends the precision and reach of multi-omics even further.

Challenges in multi-omics: Sample preparation and instrument design

Traditionally, multi-omics approaches have layered one ome over another after splitting samples for different analyses early in the pipeline, with each omic tool requiring bespoke sample extraction and preparation processing. Computational tools then attempt to correlate information from the different omics datasets.

Large-scale consortia such as the Encyclopaedia of DNA Elements (ENCODE) and The Cancer Genome Atlas (TCGA) have used this layered omics approach to fuel countless discoveries, but this method generally falls short of generating complex clinical insights from precisely the same cell populations.

Instead, the holy grail of multi-omics is to use the same cells to simultaneously extract different biomolecules and generate information about entire omes, not partial read-outs, by sequencing DNA, RNA and proteins, either on the same instrument or in a way that they can be easily integrated.

The advantage is that the data generated from this analysis would come from one source, so there would no longer be a need to speculate on how each component is related using convoluted data analysis.

But this level of simultaneous multi-omics data generation remains a feat that is incredibly difficult to achieve, especially at the single-cell level.

How can we coextract sufficient quantities of multiple different biomolecules simultaneously from the same samples for a meaningful experiment? DNA, RNA and protein molecules degrade at wildly different rates due to the wide variety of physical, chemical and enzymatic challenges thrown at them during standard storage, extraction or sample preparations. Furthermore, current DNA extraction kits generally fall short for protein extraction and vice versa.

Indeed, assays are moving in the right direction and often provide full genomic or transcriptomic read-outs, but to date only limited proteomic information for a handful of pre-selected proteins isolated with antibodies for example. This is tantamount to using NGS for DNA and RNA but only qPCR for proteins.

This partial proteomics read-out is a crucial limitation for large-scale exploratory drug discovery where prior knowledge of disease biomarkers or novel drug targets is limited. While proteomics is still an evolving arena, larger panels and Next Generation Proteomics technologies are gaining traction, as evidenced by the valuations of several proteomics companies in recent M&A.

Nevertheless, there is tremendous scope for further technological innovation for genuinely multi-omic technologies where proteomics can be performed alongside a genomic read-out.

Opportunities for the future

Opportunities abound to develop innovative and elegant solutions to address these challenges, whether in sample preparation, assay development or instrument design.

But doing so will require the collaboration of multidisciplinary teams with deep specialised market knowledge that can overcome the difficulties that will arise when different omics worlds collide. Ultimately, bridging the knowledge gap with development partners already deeply experienced in multiple omics areas will make powerful innovation possible.

The Technology Partnership is a community of experts, from engineers and physicists to biotechnologists and biochemists, each ready to collaborate to solve multi-omic challenges in diverse industrial omics workflows. Get in touch with us to find out more.

Lauren Laing
Head of Omics