Decoding Molecular Circuits of Life for the Benefit of Patients and Discovery of Intelligent Technologies
We ask: what are the laws within and between cells governing and protecting living organisms from avoiding atomic chaos & disorder thereby producing ultimately “intelligent” structures over time? In more recent vocabulary this can formulated as fundamental questions such as – what constitutes is the identity of a primary cell, what are rules governing genomic and cellular circuits and dynamics within primary human cells over time, how are these circuits regulated and to what extent can they be reprogrammed. How does order emerge within and between cells? Furthermore, we ask how can we develop methods to enable us to discover such “laws” from data?
Our motivation derives from our quest of obtaining fundamental insights of circuits of life beyond physics (i.e. elementary particles) and to exploit this from both a technological and clinical point-of-view. The underlying assumption is that having such “laws” in our hands will provide humanity with unprecedented opportunities for early detection, prevention, treatment of diseases and increased wellness. Mutatis mutandis, an understanding of “emergence of order” w.r.t circuits of life entails discovery of technological possibilities and intelligent systems beyond current imagination.
Background: Dirac wrote already in 1931 (Quantised Singularities in the Electromagnetic Field) that “There are at present fundamental problems in theoretical physics awaiting solution, e.g., the relativistic formulation of quantum mechanics and the nature of atomic nuclei (to be followed by more diﬃcult ones such as the problem of life), the solution of which problems will presumably require a more drastic revision of our fundamental concepts than any that have gone before. Quite likely these changes will be so great that it will be beyond the power of human intelligence to get the necessary new ideas by direct attempts to formulate the experimental data in mathematical terms.”
The “problem of life” as further explicated by Schrödinger in his classic book (What is life 1944) essentially comes down in two parts. First the notion of “hereditary codescript” leading to chromosomes and a discussion on how genetic information can be transferred across generations. Secondly, Schrödinger wrote “An organism's astonishing gift of concentrating a 'stream of order' on itself and thus escaping that the decay into atomic chaos -of 'drinking orderliness' from a suitable environment –seems to be connected with the presence of the 'aperiodic solids', the chromosome molecules, which doubtless represent the highest degree of well-ordered atomic association we know of - much higher than the ordinary periodic crystal - in virtue of the individual role every atom and every radical is playing here. To put it briefly, we witness the event that existing order displays the power of maintaining itself and of producing orderly events.”
The first question is reasonable well understood, albeit we can expect further surprises w.r.t epigenetic reprogramming of how the DNA is used across generations. The second question is still very open.
Our program: We address our questions by employing a dialectical method, embracing and contrasting experiments, theory, and computation. On the experimental biological side we investigate fundamental molecular mechanisms governing the development and differentiation of different types of T-cells and B-cells. These are accessible cells of fundamental importance for human health. For this work we need practical computational tools and fresh fundamental theory on how to analyze, integrate, and model such complex multifaceted data. This work guides us in our quest of understanding fundamentals of cellular life and complex living systems.
Our program targets and entails several Clinical and Technological applications. Since immunity can operate as a causal driver or responder to disease including specific processes such as chronic inflammation, neuro-degeneration, and tumor growth, immunity provides a useful window into monitoring, diagnosing, preventing disease and promoting wellness. This work includes Multiple Sclerosis, Melanoma, Rheumatoid Arthritis, Glioblastoma, Parkinson, Alzheimers disease, and Aging & development of Frailty. We use extensive data from clinical records and registers to analyze relationships between diseases and the evolution of these disease networks over time. The integrative methods we develop and use target how to extract causal models from data thus having applications in technical systems beyond the life science domain. Machine reasoning and learning models of the external world including data is of fundamental interest for our team. We triangulate this fundamental and applied work with a business and innovation perspective as several of the tools and problems we work on have wide generic applicability outside their specific initial domain of consideration.
Examples of fundamental and applied projects include:
Which cellular factors controls differentiation into different sub-types of T-cells? Mechanisms of suppression exerted by Tregulatory cells are of interest as well as the involvement of these mechanisms in diseases. How can we induce Tregulatory cells? What controls transitions of Bcells from cycling pre-Bcell stage to resting pre-Bcells? How do different levels of regulatory mechanisms interact and control dynamics of cells, tissues, and organisms? How can we understand, detect, and analyze networks? Inference of causality and interplay between structure and dynamics are recurring themes in several projects. How can we exploit such insights in the design of novel technologies and systems? Similarly, our ambition is to use this in translational projects targeting diseases and understanding wellness. A core concept is to include time in our analysis in order to extract structure out of complex living regulatory systems.
Techniques include: FACS, RT-PCR, differentiation, co-culture experiments, suppression assay, omics profiling, RNAseq, chromatin profiling, single-cell techniques, ATAC-seq, clinical samples, bioinformatics, computational modeling, data-base management and construction, big data analytics, algorithmic information theory, network analysis, Bayesian, genetics, reverse engineering, and causality techniques.
Resources in the Lab:
- We are linked to several overarching research networks of relevance to different aspects of these projects. These include CaSYM, systems medicine web-hub , CERIC, BILS, and SeRC
- Fully equipped molecular biology laboratory: Bioanalyzer, Western Blot, RT-PCR, RNA and protein isolation for the experimental work.
- A compmed HighSeq 2500 machine (not a core facility). We build libraries; perform RNA sequencing, DNA methylation or splice analysis within the lab targeting selected in-house or collaborative projects.
- In house developed software platform, TMedFusion, for management and integration of molecular and clinical data.
- Access to the core facilities within the Center for Molecular Medicine (CMM) such as cell incubation, flow cytometry analysis and cell sorting.
- Computational equipment that is equivalent to a computational cluster of 72 cores, 352 Gb of RAM and more than 35Tb for storage. Numerous scripts, know-how, and pipelines for bioinformatics and systems analysis of data. Accounts in Swedish Supercomputing National Resources such as UppNext. All software, tools and computational infrastructure for databases and integrative analysis are in place.