Takumi Lab | Kobe University School of Medicine


Towards a molecular understanding of the brain and mind

Understanding the biology of the human mind is a complex task. With the human genome sequence now available, however, describing the human mind in terms of sets of genes may no longer be just a dream. The laboratory is interested in the molecular basis of brain functions, including cognition as well as their neural circuits.

Approaches to understand the pathophysiology of neuropsychiatric disorders

The human mind and its cognitive functions are difficult to approach using molecular biology techniques because as of yet, no appropriate assay systems have been established. Due to this fundamental disadvantage, at present we can only quantify pathophysiological phenomena associated with a few higher brain functions such as learning and memory. Even if we could identify candidate genes for psychiatric disorders and make targeted mouse models, we do not know if these mice are truly representative of the human diseases. Genetics, on the other hand, provides a powerful tool for producing the molecules of the in vivo phenomena. To understand mental or cognitive functions, we must utilize data on the genetics of psychiatric diseases such as autism spectrum disorder (ASD) and schizophrenia in humans, because we can only definitively make diagnoses of these psychiatric diseases in humans. Mental illnesses are heterogeneous, however, and no objective diagnostic methods for their identification, such as blood tests or brain imaging, are currently used clinically. Because of this, we have used cutting-edge embryonic stem cell technologies to make model mice with human biological abnormalities, such as copy number variations (CNV), based on clinical data. The mice will be founders for forward genetics and targets for multi-dimensional approaches. More recently, we have also employed new genome editing techniques such as CRISPR/Cas to develop a next generation chromosome engineering method. This new technology enables us to generate whole libraries of human CNV as well as new mouse models.

Through multi-faceted approaches including electrophysiology, imaging techniques and optogenetics, we are trying to understand the neural circuits involved in social behavior using a humanized mouse model of ASD. The imaging techniques include in vivo imaging of spines by using two-photon microscopy, in vivo Ca imaging by micro-endoscope and dynamic cortical imaging using virtual reality system, etc. At the cellular level, we are also interested in local translation in neuronal dendrites and spines. As mentioned, we plan to generate a whole cell library of human CNV by using a next generation chromosome engineering technique. The library will be useful for analyzing cellular phenotypes, and for a drug screening for ASD. We also develop organoids to see their phenotypes as well as different kinds of differentiated cell types.

Recent medical research into a variety of diseases including cancer and lifestyle diseases has inspired a new theory on chronic inflammatory diseases in general. We believe psychiatric disorders are also caused by chronic inflammation, and are seeking a new paradigm of the pathophysiology of ASD in terms of an immunological basis including microbiota.

The circadian system and neural function

In contrast to the above complex brain functions, circadian rhythms are relatively simple, and we now know that mutations in clock genes cause abnormal behaviors in vivo, in multiple organisms, from Drosophila to humans. Also, we have appropriate quantitative assay systems both in vivo and in vitro. The output of the circadian clock affects various physiological phenomena such as the sleep-wake cycle, hormone secretion, and even mental states. Disturbance of the biological clock may also be related to psychiatric disorders such as seasonal affective disorder and ASD. Using the well-established systems of circadian rhythms and their basis in the canonical clock genes, we approach mental states through the light of biological clocks.

Dry Approach

Needless to say, dry approaches including mathematical modeling, computer science, bioinformatics and information science, such as AI, are essential in all of the above fields, and are used to complement our wet lab work.