The goal of our group's work is to create data-based models that show how the human host and the microbiome develop together under different conditions toward health or disease. In order to be able to interpret and make use of all this data, we have to distinguish between causality and correlation, and also between effects that result from treatment and those that result from the disease.
To achieve this, we are analyzing data gained using high-throughput methods from human hosts and microbiome, taking into account metadata on disease development, nutrition, and lifestyle. The goal is to achieve a highly accurate, quantitative understanding of host-microbiome interaction that can be translated into personalized therapies for the future.
Many questions remain unanswered qualitatively regarding the host-microbiome interaction space in the progression or reversal of disease. More importantly, high-fidelity quantitative understanding, which could be translated into personalized intervention regimes, is currently not available. The mission of the Forslund lab at the ECRC (joint cooperation of Max-Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin Berlin) is to provide this. We conduct integrative analysis of high-throughput host (metabolomic, immunomic, transcriptomic) and microbiome (metagenomic, metatranscriptomic) big data spaces, under constraints from clinical, dietary and lifestyle metadata, to try to model outcome of disease progression of treatment.
The following thus are our core activities:
Multi-omics clinical cohort studies
Systems medical analysis requires large-scale data collection from clinical cohorts. As previously reported, demographics of sampling and treatment regimes, alongside intrinsically high inter-individual variability, each may substantially bias such data, so we have particular interest in strategies for managing such bias. In particular, we seek to initiate and participate in longitudinal and interventional cohort studies to complement, enrich and synergize with existing cross-sectional/case-control datasets. Technical variability and the human factor makes standardized practices for sampling, enrolment, phenotyping, logistics and processing central to the effort of being able to usefully integrate data at high fidelity. Drawing on experiences from several international research consortia and best practices established together with our collaboration partners, we consider this a major focus.
High-throughput measurement of host and microbiota
Working with core facility actors for those procedures already standardized, we can process biosamples using a variety of methods, with a particular focus on gut microbiotal quantification using deep shotgun sequencing. With these platforms established, we welcome collaborations also in pursuit of scientific and medical questions outside of our core interests, locally and globally. This also includes adding dimensions of microbiome analysis to study cohorts where such provides a meaningful extension, and we are looking into analogous methods for analysis of e.g. host immune cell populations.
Bioinformatics and systems biology
Central to our platform is the computational analysis of high-dimensional biological (“-omics”) data, especially integrating multiple data types while controlling for complex confounder profiles. Vast amounts of work done by researchers world-wide languish in “data tombs” after initial publication; we seek to remedy this waste by systematically contrasting new findings to this background. These efforts, as well as the statistical analysis and modeling of data from new cohort studies, requires substantial software infrastructure as well as the application of machine learning, data alchemy and visualization approaches. Here we develop, benchmark and deploy software tools as needed to accomplish our aims. Moreover, all such analysis is built on a foundation of detailed and systematic annotation of human, animal and microbial biological parts, especially annotation of the genetic basis for functional pathways and processes. Where most expedient, we contribute ourselves to these annotations by mobilizing and developing techniques from evolutionary bioinformatics. With these platforms in place, we are also happy to act as computational partners in collaborative projects.
Validation and translational applications
Ultimately our mission as part of the ECRC is to facilitate the eventual translation of basic science findings into diagnostic, prognostic and therapeutic tools. For this purpose, we work closely with experimentalist collaborators, including model system experts at the MDC, seeking to validate key findings at the highest level of certainty. This involves techniques such as comparative interventions in germ-free or otherwise controlled animals, and the trialing of interventions in human volunteers. We are further very happy to work with industry partners (e.g. pharmaceutical, probiotic manufacturers, manufacturers of testing kits) in discovery or optimization of compounds, agents or techniques.
Who are you?
- Are you a student looking to do an internship, degree project or PhD studentship, or a doctor of philosophy or medicine looking to do a post-doctoral project? Whether you come from a computational background looking to apply your skills to biological and medical problems, or from a molecular biology, microbiology or medical background looking to learn high-throughput computational biology techniques, approach us to discuss ideas.
- Are you a clinician or experimentalist with an idea, cohort, set of samples or pile of data looking for help to bring it all the way to a translatable and published finding? Approach us for a collaboration, where we will together identify the most synergistic use of our respective skills and resources for furthering knowledge and empowering medicine.
- Are you a scientific leader looking to bring together a consortium of partner labs for addressing a topic thematically aligned with our focus areas, or where our contribution would be a good fit? Approach us for participation at any stage of the process, from planning to grant writing to execution.
- Are you an investor or industry actor with a potentially marketable product, but concerns remaining in the way of its maturation? Approach us for discussing these ideas (in formal confidence as needed) and perhaps plan a strategy together for working through those remaining hurdles.
We’re looking for a PhD student in computational systems biology.
Fairness, diversity, transparency and accountability in the pursuit of knowledge
The Forslund lab as an ECRC actor adheres to the MDC principles of. We are dedicated to setting a good example as a scientific environment where talented students, researchers and collaborators can flourish, grow and succeed independently of their national or ethnic background, functional variation, sex/gender identity/alignment/orientation, family configuration, or other such feature of their persons or contexts. This involves enthusiastic adherence to , and an intention to pursue direct and explicit communication of needs, expectations and intentions. Beyond the baseline provided by our host institution, the lab has its own Code of Conduct addressing many of these topics, to which all members are required to commit during their time with us.